Circadian Measures and Cognition
Megan McMahon
9/11/2019
R Markdown
library(readr)
rpx <- read_csv("~/Box/CogNeuroLab/Aging Decision Making R01/Data/Actigraphy/Combined Export File.csv")## Warning: Missing column names filled in: 'X30' [30]## Parsed with column specification:
## cols(
## .default = col_double(),
## analysis_name = col_character(),
## subject_id = col_integer(),
## data_start_date = col_character(),
## data_start_time = col_time(format = ""),
## interval_type = col_character(),
## interval_number = col_character(),
## start_date = col_character(),
## start_time = col_character(),
## end_date = col_character(),
## end_time = col_character(),
## X30 = col_character()
## )## See spec(...) for full column specifications.## Warning in rbind(names(probs), probs_f): number of columns of result is not
## a multiple of vector length (arg 1)## Warning: 12 parsing failures.
## row # A tibble: 5 x 5 col row col expected actual file expected <int> <chr> <chr> <chr> <chr> actual 1 9621 subject… an integ… Pilot '~/Box/CogNeuroLab/Aging Decision Makin… file 2 9622 subject… an integ… Pilot '~/Box/CogNeuroLab/Aging Decision Makin… row 3 9623 subject… an integ… Pilot '~/Box/CogNeuroLab/Aging Decision Makin… col 4 9624 subject… an integ… Pilot '~/Box/CogNeuroLab/Aging Decision Makin… expected 5 9625 subject… an integ… Pilot '~/Box/CogNeuroLab/Aging Decision Makin…
## ... ................. ... .......................................................................... ........ .......................................................................... ...... .......................................................................... .... .......................................................................... ... .......................................................................... ... .......................................................................... ........ ..........................................................................
## See problems(...) for more details.efficiency <- aggregate(efficiency ~ subject_id, rpx, mean, na.action = na.omit)
sleep_time <- aggregate(sleep_time ~ subject_id, rpx, mean, na.action = na.omit)
percent_wake <- aggregate(percent_wake ~ subject_id, rpx, mean, na.action = na.omit)
onset_latency <- aggregate(onset_latency ~ subject_id, rpx, mean, na.action = na.omit)
total_ac <- aggregate(total_ac ~ subject_id, rpx, mean, na.action = na.omit)
rpx2 <- merge(efficiency, sleep_time, by = 'subject_id')
rpx2 <- merge(rpx2, percent_wake, by = 'subject_id')
rpx2 <- merge(rpx2, onset_latency, by = 'subject_id')
rpx2 <- merge(rpx2, total_ac, by = 'subject_id')
head(rpx2)## subject_id efficiency sleep_time percent_wake onset_latency total_ac
## 1 30003 60.87938 256.9579 44.57318 28.659375 224642.1
## 2 30004 76.92000 335.6575 36.54286 9.823333 133108.1
## 3 30008 72.66813 341.6363 36.91493 40.873750 121651.0
## 4 30009 75.77800 308.7515 39.15000 8.966667 186779.0
## 5 30012 76.95733 311.9442 39.12548 10.124667 177709.2
## 6 30015 75.60062 315.6144 39.06553 25.420313 135299.1cr <- read_csv('~/Box/CogNeuroLab/Aging Decision Making R01/Data/CR/circadian_rhythms_2019-09-07.csv')## Parsed with column specification:
## cols(
## .default = col_double(),
## record_id = col_integer(),
## L5_starttime = col_time(format = ""),
## M10_starttime = col_time(format = "")
## )
## See spec(...) for full column specifications.cr$actquot <- cr$actamp/cr$actmesor
neuro <- read_csv('~/Box/CogNeuroLab/Aging Decision Making R01/Data/Neuropsych/AgingDecMemNeuropsyc_DATA_2019-06-12_0708.csv')## Parsed with column specification:
## cols(
## .default = col_integer(),
## education = col_double(),
## cvlt_b_zscore = col_double(),
## cvlt_sdelay_recall_zscore = col_double(),
## cvlt_sdelay_cued_zscore = col_double(),
## cvlt_ldelay_recall_zscore = col_double(),
## cvlt_ldelay_cue_recall_zscore = col_double(),
## repetitions2_828 = col_double(),
## intrusions2_c77 = col_double(),
## cvlt_recognition_hits_zscore = col_double(),
## cvlt_recognition_fp_zscore = col_double(),
## cvlt_zscore = col_double(),
## vc_per_rank = col_double(),
## vc_zscore = col_double(),
## ds_per_rank = col_double(),
## ds_zscore = col_double(),
## i_stroop_agecorrected = col_double(),
## stoop_i_zscore = col_double(),
## cowat_mean = col_double(),
## cowat_sd = col_double(),
## cowat_zscore = col_double()
## # ... with 4 more columns
## )
## See spec(...) for full column specifications.bct <- read_csv('~/Box/CogNeuroLab/Aging Decision Making R01/Analysis/bct/bct_x.csv')## Parsed with column specification:
## cols(
## record_id = col_integer(),
## wb_clustering_x = col_double(),
## wb_efficiency_x = col_double(),
## wb_modularity_x = col_double(),
## wb_participation_x = col_double(),
## wb_betweenness_x = col_double(),
## dmn_clustering_x = col_double(),
## dmn_efficiency_x = col_double(),
## dmn_modularity_x = col_double(),
## dmn_participation_x = col_double(),
## dmn_betweenness_x = col_double(),
## fpn_clustering_x = col_double(),
## fpn_efficiency_x = col_double(),
## fpn_modularity_x = col_double(),
## fpn_participation_x = col_double(),
## fpn_betweenness_x = col_double()
## )d <- merge(cr, neuro, by='record_id', all=TRUE)
d <- merge(d, bct, by='record_id', all=TRUE)
d <- merge(d, rpx2, by.x = 'record_id', by.y = 'subject_id', all=TRUE)
d$group <- factor(ifelse(d$record_id < 40000, 0, 1))Including Plots
You can also embed plots, for example:
library(formattable)
d %>%
select(age, IS:fact, group) %>%
group_by(group) %>%
summary() ## age IS IV RA
## Min. :18.00 Min. :0.0300 Min. :0.3800 Min. :0.1700
## 1st Qu.:21.00 1st Qu.:0.3425 1st Qu.:0.6700 1st Qu.:0.8100
## Median :60.00 Median :0.4400 Median :0.8700 Median :0.8700
## Mean :46.81 Mean :0.4305 Mean :0.8819 Mean :0.8340
## 3rd Qu.:68.00 3rd Qu.:0.5275 3rd Qu.:1.0475 3rd Qu.:0.9275
## Max. :91.00 Max. :0.7900 Max. :1.6600 Max. :1.0000
## NA's :5 NA's :16 NA's :16 NA's :16
## L5 L5_starttime M10 M10_starttime
## Min. : 0.000 Length:134 Min. : 34.58 Length:134
## 1st Qu.: 6.067 Class1:hms 1st Qu.:124.58 Class1:hms
## Median :10.370 Class2:difftime Median :158.68 Class2:difftime
## Mean :14.174 Mode :numeric Mean :159.16 Mode :numeric
## 3rd Qu.:15.530 3rd Qu.:186.56
## Max. :66.690 Max. :291.28
## NA's :16 NA's :16
## actamp actbeta actphi actmin
## Min. :1.000 Min. : 0.9178 Min. :10.54 Min. :0.0000
## 1st Qu.:1.370 1st Qu.: 4.7452 1st Qu.:14.44 1st Qu.:0.0000
## Median :1.529 Median : 7.3160 Median :15.55 Median :0.1084
## Mean :1.515 Mean : 10.1289 Mean :15.57 Mean :0.1557
## 3rd Qu.:1.703 3rd Qu.: 10.3520 3rd Qu.:16.60 3rd Qu.:0.2272
## Max. :2.104 Max. :132.4992 Max. :19.57 Max. :0.7636
## NA's :17 NA's :17 NA's :17 NA's :17
## actmesor actupmesor actdownmesor actalph
## Min. :0.5000 Min. : 2.721 Min. :17.09 Min. :-1.0000
## 1st Qu.:0.7997 1st Qu.: 6.393 1st Qu.:22.30 1st Qu.:-0.5764
## Median :0.9092 Median : 7.704 Median :23.29 Median :-0.4825
## Mean :0.9132 Mean : 7.737 Mean :23.40 Mean :-0.4631
## 3rd Qu.:0.9917 3rd Qu.: 8.805 3rd Qu.:24.62 3rd Qu.:-0.3996
## Max. :1.3158 Max. :14.749 Max. :28.51 Max. : 0.9533
## NA's :17 NA's :17 NA's :17 NA's :17
## actwidthratio rsqact fact group
## Min. :0.09767 Min. :0.03402 Min. : 178.4 0:60
## 1st Qu.:0.62645 1st Qu.:0.27017 1st Qu.:2664.9 1:74
## Median :0.65938 Median :0.35294 Median :3913.0
## Mean :0.65251 Mean :0.33846 Mean :4016.6
## 3rd Qu.:0.69286 3rd Qu.:0.41095 3rd Qu.:5079.7
## Max. :0.79392 Max. :0.57014 Max. :9548.0
## NA's :17 NA's :17 NA's :17d %>%
filter(group == 1) %>%
select(age, IS:fact) %>%
summary()## age IS IV RA
## Min. :60.00 Min. :0.1000 Min. :0.3800 Min. :0.2700
## 1st Qu.:64.00 1st Qu.:0.3775 1st Qu.:0.6375 1st Qu.:0.8175
## Median :67.00 Median :0.5050 Median :0.8350 Median :0.8600
## Mean :68.78 Mean :0.4667 Mean :0.8608 Mean :0.8331
## 3rd Qu.:72.00 3rd Qu.:0.5525 3rd Qu.:1.0350 3rd Qu.:0.9150
## Max. :91.00 Max. :0.7900 Max. :1.6600 Max. :0.9700
## NA's :5 NA's :10 NA's :10 NA's :10
## L5 L5_starttime M10 M10_starttime
## Min. : 2.18 Length:74 Min. : 34.58 Length:74
## 1st Qu.: 5.80 Class1:hms 1st Qu.:113.32 Class1:hms
## Median :10.11 Class2:difftime Median :149.50 Class2:difftime
## Mean :13.09 Mode :numeric Mean :149.84 Mode :numeric
## 3rd Qu.:15.24 3rd Qu.:177.38
## Max. :65.86 Max. :291.28
## NA's :10 NA's :10
## actamp actbeta actphi actmin
## Min. :1.000 Min. : 0.9178 Min. :10.54 Min. :0.0000
## 1st Qu.:1.278 1st Qu.: 4.6566 1st Qu.:13.87 1st Qu.:0.0331
## Median :1.493 Median : 8.4566 Median :14.73 Median :0.1141
## Mean :1.472 Mean : 12.4544 Mean :14.80 Mean :0.1659
## 3rd Qu.:1.682 3rd Qu.: 13.0742 3rd Qu.:15.69 3rd Qu.:0.2203
## Max. :2.027 Max. :132.4992 Max. :18.64 Max. :0.7425
## NA's :11 NA's :11 NA's :11 NA's :11
## actmesor actupmesor actdownmesor actalph
## Min. :0.5000 Min. : 2.721 Min. :17.09 Min. :-0.7976
## 1st Qu.:0.7894 1st Qu.: 6.104 1st Qu.:21.60 1st Qu.:-0.5458
## Median :0.8839 Median : 7.081 Median :22.49 Median :-0.4567
## Mean :0.9018 Mean : 7.108 Mean :22.50 Mean :-0.4255
## 3rd Qu.:1.0036 3rd Qu.: 7.956 3rd Qu.:23.55 3rd Qu.:-0.3507
## Max. :1.3158 Max. :14.749 Max. :27.02 Max. : 0.9533
## NA's :11 NA's :11 NA's :11 NA's :11
## actwidthratio rsqact fact
## Min. :0.09767 Min. :0.03402 Min. : 178.4
## 1st Qu.:0.61407 1st Qu.:0.27409 1st Qu.:2719.7
## Median :0.65097 Median :0.36583 Median :4119.7
## Mean :0.64128 Mean :0.34312 Mean :4131.0
## 3rd Qu.:0.68379 3rd Qu.:0.41425 3rd Qu.:5168.6
## Max. :0.79392 Max. :0.57014 Max. :9548.0
## NA's :11 NA's :11 NA's :11d.mlt <- melt(select(d, record_id, group, IS:actquot, -rsqact, -fnlrgact, -L5_starttime, -M10_starttime), id.vars=c('record_id', 'group'))
ggplot(data = d.mlt, aes(x = variable, y = value, group = group)) +
geom_violin(aes(fill = group)) +
facet_wrap( ~ variable, scales='free') +
theme_minimal() +
scale_fill_manual(values = brewer.pal(8, "Paired")[7:8], name = 'Age Group', labels = c('Young Adults', 'Older Adults')) +
xlab(element_blank()) + ylab(element_blank())## Warning: Removed 267 rows containing non-finite values (stat_ydensity).
#Effect of age on circadian variables
#Older Adults
summary(lm(actamp ~ age, data = d[d$group == 1,])) #p = 0.0119##
## Call:
## lm(formula = actamp ~ age, data = d[d$group == 1, ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.52866 -0.15392 0.00052 0.18067 0.49516
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.392135 0.357238 6.696 1.02e-08 ***
## age -0.013492 0.005193 -2.598 0.0119 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2641 on 57 degrees of freedom
## (15 observations deleted due to missingness)
## Multiple R-squared: 0.1059, Adjusted R-squared: 0.0902
## F-statistic: 6.75 on 1 and 57 DF, p-value: 0.01191summary(lm(fact ~ age, data = d[d$group == 1,])) #p = 0.024507##
## Call:
## lm(formula = fact ~ age, data = d[d$group == 1, ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4368.1 -1241.7 -205.1 1115.5 5092.7
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 10375.77 2712.08 3.826 0.000326 ***
## age -91.08 39.42 -2.310 0.024507 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2005 on 57 degrees of freedom
## (15 observations deleted due to missingness)
## Multiple R-squared: 0.08563, Adjusted R-squared: 0.06959
## F-statistic: 5.338 on 1 and 57 DF, p-value: 0.02451summary(lm(actupmesor ~ age, data = d[d$group == 1,])) #NS##
## Call:
## lm(formula = actupmesor ~ age, data = d[d$group == 1, ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.5526 -0.9929 -0.1135 0.9229 7.4358
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.84936 2.53471 3.886 0.000268 ***
## age -0.03963 0.03684 -1.076 0.286601
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.874 on 57 degrees of freedom
## (15 observations deleted due to missingness)
## Multiple R-squared: 0.0199, Adjusted R-squared: 0.002701
## F-statistic: 1.157 on 1 and 57 DF, p-value: 0.2866summary(lm(actdownmesor ~ age, data = d[d$group == 1,])) #NS##
## Call:
## lm(formula = actdownmesor ~ age, data = d[d$group == 1, ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.3648 -0.9937 0.0731 1.0261 4.4114
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 21.834009 2.477457 8.813 3.12e-12 ***
## age 0.009744 0.036013 0.271 0.788
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.832 on 57 degrees of freedom
## (15 observations deleted due to missingness)
## Multiple R-squared: 0.001283, Adjusted R-squared: -0.01624
## F-statistic: 0.07321 on 1 and 57 DF, p-value: 0.7877summary(lm(RA ~ age, data = d[d$group == 1,])) #NS##
## Call:
## lm(formula = RA ~ age, data = d[d$group == 1, ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.47173 -0.01832 0.02736 0.08782 0.12931
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.8248210 0.1692245 4.874 8.84e-06 ***
## age 0.0002601 0.0024547 0.106 0.916
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1266 on 58 degrees of freedom
## (14 observations deleted due to missingness)
## Multiple R-squared: 0.0001935, Adjusted R-squared: -0.01704
## F-statistic: 0.01123 on 1 and 58 DF, p-value: 0.916summary(lm(IS ~ age, data = d[d$group == 1,])) #NS##
## Call:
## lm(formula = IS ~ age, data = d[d$group == 1, ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.37044 -0.11336 0.02350 0.09238 0.30658
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.674048 0.201030 3.353 0.00141 **
## age -0.002979 0.002916 -1.021 0.31128
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1503 on 58 degrees of freedom
## (14 observations deleted due to missingness)
## Multiple R-squared: 0.01767, Adjusted R-squared: 0.0007343
## F-statistic: 1.043 on 1 and 58 DF, p-value: 0.3113summary(lm(IV ~ age, data = d[d$group == 1,])) # p = 0.08##
## Call:
## lm(formula = IV ~ age, data = d[d$group == 1, ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.45774 -0.20770 -0.03235 0.18472 0.72099
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.230124 0.363957 0.632 0.5297
## age 0.009206 0.005279 1.744 0.0865 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2722 on 58 degrees of freedom
## (14 observations deleted due to missingness)
## Multiple R-squared: 0.04982, Adjusted R-squared: 0.03343
## F-statistic: 3.041 on 1 and 58 DF, p-value: 0.08649#Younger Adults
summary(lm(actamp ~ age, data = d[d$group == 0,])) #NS##
## Call:
## lm(formula = actamp ~ age, data = d[d$group == 0, ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.54283 -0.10441 -0.01082 0.14652 0.54349
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.359623 0.194918 6.975 5.42e-09 ***
## age 0.009584 0.008938 1.072 0.289
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2401 on 52 degrees of freedom
## (6 observations deleted due to missingness)
## Multiple R-squared: 0.02163, Adjusted R-squared: 0.002818
## F-statistic: 1.15 on 1 and 52 DF, p-value: 0.2885summary(lm(fact ~ age, data = d[d$group == 0,])) #NS##
## Call:
## lm(formula = fact ~ age, data = d[d$group == 0, ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -3010.1 -964.0 -330.9 774.8 4176.4
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1992.72 1393.37 1.430 0.159
## age 87.93 63.89 1.376 0.175
##
## Residual standard error: 1716 on 52 degrees of freedom
## (6 observations deleted due to missingness)
## Multiple R-squared: 0.03515, Adjusted R-squared: 0.01659
## F-statistic: 1.894 on 1 and 52 DF, p-value: 0.1746summary(lm(actupmesor ~ age, data = d[d$group == 0,])) #p = 0.0272##
## Call:
## lm(formula = actupmesor ~ age, data = d[d$group == 0, ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.3138 -1.0715 -0.2811 1.2755 3.9007
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 11.54640 1.37266 8.412 2.86e-11 ***
## age -0.14306 0.06294 -2.273 0.0272 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.691 on 52 degrees of freedom
## (6 observations deleted due to missingness)
## Multiple R-squared: 0.09037, Adjusted R-squared: 0.07287
## F-statistic: 5.166 on 1 and 52 DF, p-value: 0.0272summary(lm(actdownmesor ~ age, data = d[d$group == 0,])) #p = 0.0206##
## Call:
## lm(formula = actdownmesor ~ age, data = d[d$group == 0, ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.3415 -1.1730 -0.1704 0.8760 3.6074
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 27.24931 1.19120 22.876 <2e-16 ***
## age -0.13042 0.05462 -2.388 0.0206 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.467 on 52 degrees of freedom
## (6 observations deleted due to missingness)
## Multiple R-squared: 0.09881, Adjusted R-squared: 0.08148
## F-statistic: 5.702 on 1 and 52 DF, p-value: 0.02062summary(lm(RA ~ age, data = d[d$group == 0,])) #NS##
## Call:
## lm(formula = RA ~ age, data = d[d$group == 0, ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.66963 -0.03269 0.04617 0.09231 0.17271
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.768697 0.118702 6.476 3.39e-08 ***
## age 0.003084 0.005443 0.567 0.573
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1462 on 52 degrees of freedom
## (6 observations deleted due to missingness)
## Multiple R-squared: 0.006135, Adjusted R-squared: -0.01298
## F-statistic: 0.321 on 1 and 52 DF, p-value: 0.5734summary(lm(IS ~ age, data = d[d$group == 0,])) #NS##
## Call:
## lm(formula = IS ~ age, data = d[d$group == 0, ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.35814 -0.05518 0.01649 0.06277 0.19369
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3796958 0.0884178 4.294 7.67e-05 ***
## age 0.0003673 0.0040543 0.091 0.928
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1089 on 52 degrees of freedom
## (6 observations deleted due to missingness)
## Multiple R-squared: 0.0001578, Adjusted R-squared: -0.01907
## F-statistic: 0.008207 on 1 and 52 DF, p-value: 0.9282summary(lm(IV ~ age, data = d[d$group == 0,])) #NS##
## Call:
## lm(formula = IV ~ age, data = d[d$group == 0, ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.51102 -0.16389 0.00232 0.13482 0.63379
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.719899 0.204832 3.515 0.000922 ***
## age 0.008704 0.009392 0.927 0.358350
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2523 on 52 degrees of freedom
## (6 observations deleted due to missingness)
## Multiple R-squared: 0.01625, Adjusted R-squared: -0.002671
## F-statistic: 0.8588 on 1 and 52 DF, p-value: 0.3584# Stability from day to day
t.test(IS ~ group, data = d) # 0.00142##
## Welch Two Sample t-test
##
## data: IS by group
## t = -3.2717, df = 112.45, p-value = 0.00142
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.12704321 -0.03120911
## sample estimates:
## mean in group 0 mean in group 1
## 0.3875926 0.4667188t.test(IV ~ group, data = d)##
## Welch Two Sample t-test
##
## data: IV by group
## t = 0.95856, df = 114.94, p-value = 0.3398
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.0493299 0.1418415
## sample estimates:
## mean in group 0 mean in group 1
## 0.9070370 0.8607813t.test(RA ~ group, data = d)##
## Welch Two Sample t-test
##
## data: RA by group
## t = 0.070789, df = 111.5, p-value = 0.9437
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.05060833 0.05435833
## sample estimates:
## mean in group 0 mean in group 1
## 0.835000 0.833125t.test(actamp ~ group, data = d)##
## Welch Two Sample t-test
##
## data: actamp by group
## t = 1.951, df = 115, p-value = 0.05349
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.001432771 0.189215179
## sample estimates:
## mean in group 0 mean in group 1
## 1.565671 1.471780t.test(fact ~ group, data = d)##
## Welch Two Sample t-test
##
## data: fact by group
## t = -0.7062, df = 114.95, p-value = 0.4815
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -942.4018 447.0391
## sample estimates:
## mean in group 0 mean in group 1
## 3883.271 4130.952# Morningness preference
t.test(actphi ~ group, data = d) # p = 1.541e-08##
## Welch Two Sample t-test
##
## data: actphi by group
## t = 6.0986, df = 112.66, p-value = 1.541e-08
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 1.116990 2.191975
## sample estimates:
## mean in group 0 mean in group 1
## 16.45795 14.80347t.test(actupmesor ~ group, data = d) # p = 8.015e-05##
## Welch Two Sample t-test
##
## data: actupmesor by group
## t = 4.0923, df = 113.66, p-value = 8.015e-05
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 0.702991 2.022265
## sample estimates:
## mean in group 0 mean in group 1
## 8.470703 7.108075t.test(actdownmesor~ group, data = d) # p = 4.229e-09##
## Welch Two Sample t-test
##
## data: actdownmesor by group
## t = 6.3603, df = 115, p-value = 4.229e-09
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 1.340180 2.552494
## sample estimates:
## mean in group 0 mean in group 1
## 24.44519 22.49886wilcox.test(IS ~ group, data=d) #sig##
## Wilcoxon rank sum test with continuity correction
##
## data: IS by group
## W = 1101, p-value = 0.00071
## alternative hypothesis: true location shift is not equal to 0wilcox.test(IV ~ group, data=d)##
## Wilcoxon rank sum test with continuity correction
##
## data: IV by group
## W = 1963, p-value = 0.2052
## alternative hypothesis: true location shift is not equal to 0wilcox.test(RA ~ group, data=d)##
## Wilcoxon rank sum test with continuity correction
##
## data: RA by group
## W = 1766, p-value = 0.8393
## alternative hypothesis: true location shift is not equal to 0wilcox.test(actamp ~ group, data=d) ##
## Wilcoxon rank sum test with continuity correction
##
## data: actamp by group
## W = 2033, p-value = 0.06985
## alternative hypothesis: true location shift is not equal to 0wilcox.test(fact ~ group, data=d) ##
## Wilcoxon rank sum test with continuity correction
##
## data: fact by group
## W = 1571, p-value = 0.4789
## alternative hypothesis: true location shift is not equal to 0wilcox.test(actphi ~ group, data=d) #sig##
## Wilcoxon rank sum test with continuity correction
##
## data: actphi by group
## W = 2691, p-value = 6.302e-08
## alternative hypothesis: true location shift is not equal to 0wilcox.test(actupmesor ~ group, data=d) #sig##
## Wilcoxon rank sum test with continuity correction
##
## data: actupmesor by group
## W = 2441, p-value = 5.274e-05
## alternative hypothesis: true location shift is not equal to 0wilcox.test(actdownmesor ~ group, data=d) #sig##
## Wilcoxon rank sum test with continuity correction
##
## data: actdownmesor by group
## W = 2734, p-value = 1.651e-08
## alternative hypothesis: true location shift is not equal to 0#Sleep Measures
t.test(sleep_time ~ group, data = d) #NS##
## Welch Two Sample t-test
##
## data: sleep_time by group
## t = -1.1941, df = 119.77, p-value = 0.2348
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -61.55525 15.24012
## sample estimates:
## mean in group 0 mean in group 1
## 341.1519 364.3094t.test(percent_wake ~ group, data = d) #p = 0.03961##
## Welch Two Sample t-test
##
## data: percent_wake by group
## t = 2.0799, df = 123.44, p-value = 0.03961
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 0.08110572 3.27644073
## sample estimates:
## mean in group 0 mean in group 1
## 39.14684 37.46807t.test(onset_latency ~ group, data = d) #p = 0.0066##
## Welch Two Sample t-test
##
## data: onset_latency by group
## t = -2.768, df = 109.26, p-value = 0.006626
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -15.876576 -2.627602
## sample estimates:
## mean in group 0 mean in group 1
## 22.91220 32.16429t.test(efficiency ~ group, data = d) #NS##
## Welch Two Sample t-test
##
## data: efficiency by group
## t = 0.9489, df = 123.23, p-value = 0.3445
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -1.250580 3.553696
## sample estimates:
## mean in group 0 mean in group 1
## 72.21969 71.06813summary(lm(trails_b_z_score ~ gender + IS, data = d)) # NS##
## Call:
## lm(formula = trails_b_z_score ~ gender + IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.8257 -0.6877 0.2462 1.0938 2.8842
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.4314 0.6079 -2.355 0.0203 *
## gender 0.4484 0.3109 1.442 0.1520
## IS 1.2158 1.0799 1.126 0.2627
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.521 on 110 degrees of freedom
## (21 observations deleted due to missingness)
## Multiple R-squared: 0.03988, Adjusted R-squared: 0.02242
## F-statistic: 2.284 on 2 and 110 DF, p-value: 0.1067summary(lm(ds_backward_score ~ age + gender + IS, data = d)) # NS##
## Call:
## lm(formula = ds_backward_score ~ age + gender + IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.0663 -2.0417 -0.4274 1.5670 6.5539
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 11.543308 1.082165 10.667 <2e-16 ***
## age -0.005521 0.010548 -0.523 0.602
## gender -1.321268 0.534439 -2.472 0.015 *
## IS -0.169486 1.908391 -0.089 0.929
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.604 on 109 degrees of freedom
## (21 observations deleted due to missingness)
## Multiple R-squared: 0.06345, Adjusted R-squared: 0.03767
## F-statistic: 2.461 on 3 and 109 DF, p-value: 0.06646summary(lm(cvlt_ldelay_recall_zscore ~ IS, data = d)) # p = 0.08899##
## Call:
## lm(formula = cvlt_ldelay_recall_zscore ~ IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.3598 -0.6626 0.1178 0.6552 2.1552
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.1524 0.4261 2.705 0.00896 **
## IS -1.4956 0.8646 -1.730 0.08899 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9988 on 58 degrees of freedom
## (74 observations deleted due to missingness)
## Multiple R-squared: 0.04906, Adjusted R-squared: 0.03266
## F-statistic: 2.992 on 1 and 58 DF, p-value: 0.08899summary(lm(trails_b_z_score ~ actupmesor^2 + actupmesor, data = d)) ##
## Call:
## lm(formula = trails_b_z_score ~ actupmesor^2 + actupmesor, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.6518 -0.6030 0.2353 1.0893 2.8379
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.10264 0.60152 -1.833 0.0695 .
## actupmesor 0.11859 0.07535 1.574 0.1184
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.527 on 110 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.02203, Adjusted R-squared: 0.01313
## F-statistic: 2.477 on 1 and 110 DF, p-value: 0.1184summary(lm(ds_backward_score ~ actupmesor^2 + actupmesor, data = d)) ##
## Call:
## lm(formula = ds_backward_score ~ actupmesor^2 + actupmesor, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.3618 -1.6874 -0.3038 1.9018 6.1068
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.1689 1.0372 7.876 2.59e-12 ***
## actupmesor 0.1148 0.1293 0.888 0.377
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.641 on 110 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.007113, Adjusted R-squared: -0.001913
## F-statistic: 0.788 on 1 and 110 DF, p-value: 0.3766summary(lm(cvlt_ldelay_recall_zscore ~ actupmesor^2 + actupmesor, data = d)) ##
## Call:
## lm(formula = cvlt_ldelay_recall_zscore ~ actupmesor^2 + actupmesor,
## data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.46732 -0.52470 0.05424 0.59888 2.07220
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.65169 0.52735 1.236 0.222
## actupmesor -0.03076 0.07152 -0.430 0.669
##
## Residual standard error: 1.022 on 57 degrees of freedom
## (75 observations deleted due to missingness)
## Multiple R-squared: 0.003235, Adjusted R-squared: -0.01425
## F-statistic: 0.185 on 1 and 57 DF, p-value: 0.6687summary(lm(trails_b_z_score ~ actamp + group, data = d)) # p = 0.020397##
## Call:
## lm(formula = trails_b_z_score ~ actamp + group, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.5327 -0.7351 0.1222 1.0960 2.5738
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.5357 0.8597 -4.113 7.61e-05 ***
## actamp 1.9839 0.5345 3.712 0.000326 ***
## group1 0.6526 0.2773 2.353 0.020397 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.444 on 109 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.1335, Adjusted R-squared: 0.1176
## F-statistic: 8.399 on 2 and 109 DF, p-value: 0.000405summary(lm(ds_backward_score ~ age + gender + group + actamp, data = d)) # p = 0.0631##
## Call:
## lm(formula = ds_backward_score ~ age + gender + group + actamp,
## data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.9785 -1.5818 -0.1768 1.5840 5.8367
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 10.10461 1.98697 5.085 1.57e-06 ***
## age -0.07635 0.04496 -1.698 0.0924 .
## gender -1.31535 0.50828 -2.588 0.0110 *
## group1 3.77811 2.14156 1.764 0.0806 .
## actamp 1.76532 0.94007 1.878 0.0631 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.517 on 107 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.1223, Adjusted R-squared: 0.08953
## F-statistic: 3.729 on 4 and 107 DF, p-value: 0.007009summary(lm(cvlt_ldelay_recall_zscore ~ actamp, data = d)) # NS##
## Call:
## lm(formula = cvlt_ldelay_recall_zscore ~ actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.42885 -0.66983 0.08862 0.61260 2.32896
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.2095 0.7175 1.686 0.0973 .
## actamp -0.5294 0.4803 -1.102 0.2750
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.013 on 57 degrees of freedom
## (75 observations deleted due to missingness)
## Multiple R-squared: 0.02087, Adjusted R-squared: 0.003688
## F-statistic: 1.215 on 1 and 57 DF, p-value: 0.275summary(lm(trails_b_z_score ~ group + fact, data = d)) # p = 0.015##
## Call:
## lm(formula = trails_b_z_score ~ group + fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.9129 -0.6277 0.1647 1.1082 2.2264
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.138e+00 3.525e-01 -3.229 0.00164 **
## group1 4.212e-01 2.830e-01 1.488 0.13953
## fact 1.825e-04 7.421e-05 2.459 0.01549 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.492 on 109 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.07535, Adjusted R-squared: 0.05838
## F-statistic: 4.441 on 2 and 109 DF, p-value: 0.01399summary(lm(ds_backward_score ~ age + gender + fact, data = d)) # NS##
## Call:
## lm(formula = ds_backward_score ~ age + gender + fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.9338 -1.8536 -0.2575 1.7417 6.5404
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 11.0254573 1.0219391 10.789 < 2e-16 ***
## age -0.0042325 0.0102207 -0.414 0.67961
## gender -1.3963157 0.5250697 -2.659 0.00902 **
## fact 0.0001338 0.0001301 1.028 0.30615
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.582 on 108 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.06796, Adjusted R-squared: 0.04207
## F-statistic: 2.625 on 3 and 108 DF, p-value: 0.05418summary(lm(cvlt_ldelay_recall_zscore ~ actamp, data = d)) # NS##
## Call:
## lm(formula = cvlt_ldelay_recall_zscore ~ actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.42885 -0.66983 0.08862 0.61260 2.32896
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.2095 0.7175 1.686 0.0973 .
## actamp -0.5294 0.4803 -1.102 0.2750
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.013 on 57 degrees of freedom
## (75 observations deleted due to missingness)
## Multiple R-squared: 0.02087, Adjusted R-squared: 0.003688
## F-statistic: 1.215 on 1 and 57 DF, p-value: 0.275summary(lm(trails_b_z_score ~ group + actupmesor, data = d)) # p = 0.019##
## Call:
## lm(formula = trails_b_z_score ~ group + actupmesor, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.6562 -0.6564 0.2369 1.0148 2.5832
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -2.02499 0.70034 -2.891 0.00463 **
## group1 0.73695 0.30330 2.430 0.01674 *
## actupmesor 0.18836 0.07911 2.381 0.01901 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.495 on 109 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.07228, Adjusted R-squared: 0.05525
## F-statistic: 4.246 on 2 and 109 DF, p-value: 0.01676summary(lm(ds_backward_score ~ age + gender + group + actupmesor, data = d)) # NS##
## Call:
## lm(formula = ds_backward_score ~ age + gender + group + actupmesor,
## data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.0364 -1.8211 -0.2138 1.7493 6.1281
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 12.38834 1.83175 6.763 7.41e-10 ***
## age -0.08822 0.04566 -1.932 0.0560 .
## gender -1.20614 0.51251 -2.353 0.0204 *
## group1 4.24240 2.16383 1.961 0.0525 .
## actupmesor 0.06607 0.13643 0.484 0.6292
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.556 on 107 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.0954, Adjusted R-squared: 0.06158
## F-statistic: 2.821 on 4 and 107 DF, p-value: 0.02858summary(lm(cvlt_ldelay_recall_zscore ~ actupmesor, data = d)) # NS##
## Call:
## lm(formula = cvlt_ldelay_recall_zscore ~ actupmesor, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.46732 -0.52470 0.05424 0.59888 2.07220
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.65169 0.52735 1.236 0.222
## actupmesor -0.03076 0.07152 -0.430 0.669
##
## Residual standard error: 1.022 on 57 degrees of freedom
## (75 observations deleted due to missingness)
## Multiple R-squared: 0.003235, Adjusted R-squared: -0.01425
## F-statistic: 0.185 on 1 and 57 DF, p-value: 0.6687summary(lm(trails_b_z_score ~ group + actdownmesor, data = d)) # p = 0.01735##
## Call:
## lm(formula = trails_b_z_score ~ group + actdownmesor, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.3407 -0.5575 0.2192 0.9828 2.4270
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -5.5558 2.1315 -2.607 0.01042 *
## group1 0.8984 0.3324 2.703 0.00797 **
## actdownmesor 0.2097 0.0868 2.416 0.01735 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.493 on 109 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.07364, Adjusted R-squared: 0.05664
## F-statistic: 4.333 on 2 and 109 DF, p-value: 0.01547summary(lm(ds_backward_score ~ age + gender + group + actdownmesor, data = d)) # NS##
## Call:
## lm(formula = ds_backward_score ~ age + gender + group + actdownmesor,
## data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.1413 -1.8923 -0.2542 1.8468 6.1711
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 12.17292 3.87572 3.141 0.00218 **
## age -0.09183 0.04493 -2.044 0.04341 *
## gender -1.19452 0.51438 -2.322 0.02211 *
## group1 4.38746 2.15888 2.032 0.04460 *
## actdownmesor 0.03419 0.14498 0.236 0.81400
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.558 on 107 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.09389, Adjusted R-squared: 0.06001
## F-statistic: 2.772 on 4 and 107 DF, p-value: 0.03084summary(lm(cvlt_ldelay_recall_zscore ~ actdownmesor, data = d)) # NS##
## Call:
## lm(formula = cvlt_ldelay_recall_zscore ~ actdownmesor, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.44676 -0.44367 0.07019 0.57747 2.05556
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.572823 1.669842 0.343 0.733
## actdownmesor -0.006249 0.073974 -0.084 0.933
##
## Residual standard error: 1.024 on 57 degrees of freedom
## (75 observations deleted due to missingness)
## Multiple R-squared: 0.0001252, Adjusted R-squared: -0.01742
## F-statistic: 0.007137 on 1 and 57 DF, p-value: 0.933#No significant relationships between cognition and sleep variables
summary(lm(trails_b_z_score ~ group + sleep_time, data = d))##
## Call:
## lm(formula = trails_b_z_score ~ group + sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.5746 -0.6442 0.2112 1.1066 2.2780
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.108467 0.475809 0.228 0.8201
## group1 0.535849 0.278490 1.924 0.0567 .
## sleep_time -0.001477 0.001264 -1.169 0.2448
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.519 on 118 degrees of freedom
## (13 observations deleted due to missingness)
## Multiple R-squared: 0.03763, Adjusted R-squared: 0.02132
## F-statistic: 2.307 on 2 and 118 DF, p-value: 0.1041summary(lm(ds_backward_score ~ group + sleep_time, data = d)) ##
## Call:
## lm(formula = ds_backward_score ~ group + sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.2777 -1.8491 -0.1473 1.8479 6.0894
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.714714 0.829041 11.718 <2e-16 ***
## group1 -0.284165 0.485302 -0.586 0.559
## sleep_time -0.001676 0.002198 -0.762 0.447
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.643 on 118 degrees of freedom
## (13 observations deleted due to missingness)
## Multiple R-squared: 0.008762, Adjusted R-squared: -0.008039
## F-statistic: 0.5215 on 2 and 118 DF, p-value: 0.595summary(lm(cvlt_ldelay_recall_zscore ~ sleep_time, data = d))##
## Call:
## lm(formula = cvlt_ldelay_recall_zscore ~ sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.44978 -0.45051 0.06217 0.56969 2.02864
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2350424 0.4317497 0.544 0.588
## sleep_time 0.0005752 0.0011265 0.511 0.611
##
## Residual standard error: 1.002 on 63 degrees of freedom
## (69 observations deleted due to missingness)
## Multiple R-squared: 0.004121, Adjusted R-squared: -0.01169
## F-statistic: 0.2607 on 1 and 63 DF, p-value: 0.6114summary(lm(trails_b_z_score ~ group + percent_wake, data = d)) ##
## Call:
## lm(formula = trails_b_z_score ~ group + percent_wake, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.5416 -0.7038 0.2494 1.1092 2.4287
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.56899 1.21132 -1.295 0.1978
## group1 0.54809 0.28167 1.946 0.0541 .
## percent_wake 0.02998 0.03051 0.982 0.3279
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.522 on 118 degrees of freedom
## (13 observations deleted due to missingness)
## Multiple R-squared: 0.03438, Adjusted R-squared: 0.01802
## F-statistic: 2.101 on 2 and 118 DF, p-value: 0.1269summary(lm(ds_backward_score ~ group + percent_wake, data = d)) ##
## Call:
## lm(formula = ds_backward_score ~ group + percent_wake, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.0548 -1.9637 -0.2343 1.9179 6.2316
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 7.94440 2.10172 3.780 0.000248 ***
## group1 -0.27333 0.49146 -0.556 0.579157
## percent_wake 0.03058 0.05287 0.578 0.564047
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.646 on 118 degrees of freedom
## (13 observations deleted due to missingness)
## Multiple R-squared: 0.006695, Adjusted R-squared: -0.01014
## F-statistic: 0.3977 on 2 and 118 DF, p-value: 0.6728summary(lm(cvlt_ldelay_recall_zscore ~ percent_wake, data = d))##
## Call:
## lm(formula = cvlt_ldelay_recall_zscore ~ percent_wake, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.49062 -0.51902 0.02878 0.56434 1.92863
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.84389 0.96151 1.918 0.0597 .
## percent_wake -0.03735 0.02549 -1.466 0.1477
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9877 on 63 degrees of freedom
## (69 observations deleted due to missingness)
## Multiple R-squared: 0.03297, Adjusted R-squared: 0.01762
## F-statistic: 2.148 on 1 and 63 DF, p-value: 0.1477summary(lm(trails_b_z_score ~ group + onset_latency, data = d))##
## Call:
## lm(formula = trails_b_z_score ~ group + onset_latency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.4709 -0.6393 0.2692 1.1102 2.3662
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.456679 0.259938 -1.757 0.0815 .
## group1 0.472736 0.286496 1.650 0.1016
## onset_latency 0.002669 0.007127 0.374 0.7087
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.527 on 118 degrees of freedom
## (13 observations deleted due to missingness)
## Multiple R-squared: 0.02764, Adjusted R-squared: 0.01116
## F-statistic: 1.677 on 2 and 118 DF, p-value: 0.1913summary(lm(ds_backward_score ~ group + onset_latency, data = d))##
## Call:
## lm(formula = ds_backward_score ~ group + onset_latency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.2069 -1.8602 -0.1827 1.9115 6.2700
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9.23365 0.45388 20.344 <2e-16 ***
## group1 -0.29095 0.49628 -0.586 0.559
## onset_latency -0.00394 0.01233 -0.320 0.750
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.649 on 118 degrees of freedom
## (13 observations deleted due to missingness)
## Multiple R-squared: 0.004739, Adjusted R-squared: -0.01213
## F-statistic: 0.281 on 2 and 118 DF, p-value: 0.7556summary(lm(cvlt_ldelay_recall_zscore ~ onset_latency, data = d))##
## Call:
## lm(formula = cvlt_ldelay_recall_zscore ~ onset_latency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.45392 -0.46068 0.05358 0.56099 2.04000
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4679592 0.2104112 2.224 0.0297 *
## onset_latency -0.0006749 0.0052484 -0.129 0.8981
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.004 on 63 degrees of freedom
## (69 observations deleted due to missingness)
## Multiple R-squared: 0.0002624, Adjusted R-squared: -0.01561
## F-statistic: 0.01654 on 1 and 63 DF, p-value: 0.8981summary(lm(trails_b_z_score ~ group + efficiency, data = d)) ##
## Call:
## lm(formula = trails_b_z_score ~ group + efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.5271 -0.6562 0.1934 1.1011 2.3801
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.481437 1.465896 -0.328 0.7432
## group1 0.499804 0.279068 1.791 0.0759 .
## efficiency 0.001189 0.020103 0.059 0.9529
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.528 on 118 degrees of freedom
## (13 observations deleted due to missingness)
## Multiple R-squared: 0.02651, Adjusted R-squared: 0.01001
## F-statistic: 1.607 on 2 and 118 DF, p-value: 0.2049summary(lm(ds_backward_score ~ group + efficiency, data = d)) ##
## Call:
## lm(formula = ds_backward_score ~ group + efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.2006 -1.8251 -0.1607 1.8624 6.2539
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.60719 2.53775 3.392 0.000946 ***
## group1 -0.32033 0.48422 -0.662 0.509558
## efficiency 0.00742 0.03481 0.213 0.831567
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.649 on 118 degrees of freedom
## (13 observations deleted due to missingness)
## Multiple R-squared: 0.004261, Adjusted R-squared: -0.01262
## F-statistic: 0.2525 on 2 and 118 DF, p-value: 0.7773summary(lm(cvlt_ldelay_recall_zscore ~ efficiency, data = d)) ##
## Call:
## lm(formula = cvlt_ldelay_recall_zscore ~ efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.4653 -0.5267 0.0100 0.5654 1.9369
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.54085 1.15174 -0.470 0.640
## efficiency 0.01386 0.01608 0.862 0.392
##
## Residual standard error: 0.9986 on 63 degrees of freedom
## (69 observations deleted due to missingness)
## Multiple R-squared: 0.01166, Adjusted R-squared: -0.004032
## F-statistic: 0.743 on 1 and 63 DF, p-value: 0.392d2.mlt <- melt(select(d, record_id, group, IS:actquot, trails_b_z_score, -rsqact, -fnlrgact, -L5_starttime, -M10_starttime, -actbeta, -actwidthratio), id.vars=c('record_id', 'group', 'trails_b_z_score'))
ggplot(data = d2.mlt) +
ggtitle('Circadian Measures and TMT-B Performance') +
geom_point(aes(x = value, y = trails_b_z_score, group = group, color = group), size=0.5) +
stat_smooth(aes(x = value, y = trails_b_z_score, group = group, color = group), method = 'loess', se = FALSE, fullrange = FALSE) +
facet_wrap(~ variable, scales='free') +
theme_minimal() +
scale_color_manual(values = brewer.pal(8, "Paired")[7:8], name = 'Group', labels = c('Young Adults', 'Older Adults')) +
xlab(element_blank()) + ylab('TMT-B') +
theme(axis.text.y = element_blank(), axis.text.x = element_blank())## Warning: Removed 303 rows containing non-finite values (stat_smooth).## Warning: Removed 303 rows containing missing values (geom_point).
summary(d$actalph)## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## -1.0000 -0.5764 -0.4825 -0.4631 -0.3996 0.9533 17lm1 <- lm(trails_b_z_score ~ group + fact, data = d)
par(mfrow=c(2,2))
plot(lm1, which=1:4)
shapiro.test(lm1$residuals) #residuals not normally distributed##
## Shapiro-Wilk normality test
##
## data: lm1$residuals
## W = 0.92007, p-value = 4.849e-06lm2 <- lm(trails_b_z_score ~ group + actupmesor, data = d)
par(mfrow=c(2,2))
plot(lm2, which=1:4)
shapiro.test(lm2$residuals) #residuals not normally distributed##
## Shapiro-Wilk normality test
##
## data: lm2$residuals
## W = 0.90872, p-value = 1.177e-06trails_data <- dplyr::select(d, wb_clustering_x:fpn_betweenness_x, contains('trail'))
corrgram::corrgram(trails_data, cor.method = 'spearman', lower.panel=corrgram::panel.fill, upper.panel=corrgram::panel.cor)
ds_data <- dplyr::select(d, wb_clustering_x:fpn_betweenness_x, starts_with('ds'))
corrgram::corrgram(ds_data, cor.method = 'spearman', lower.panel=corrgram::panel.fill, upper.panel=corrgram::panel.cor)
cvlt_data <- dplyr::select(d, wb_clustering_x:fpn_betweenness_x, contains('cvlt_z'))
corrgram::corrgram(cvlt_data, cor.method = 'spearman', lower.panel=corrgram::panel.fill, upper.panel=corrgram::panel.cor)
cowat_data <- dplyr::select(d, wb_clustering_x:fpn_betweenness_x, contains('cowat'))
corrgram::corrgram(cowat_data, cor.method = 'spearman', lower.panel=corrgram::panel.fill, upper.panel=corrgram::panel.cor)
stroop_data <- dplyr::select(d, wb_clustering_x:fpn_betweenness_x, contains('stroop'))
corrgram::corrgram(stroop_data, cor.method = 'spearman', lower.panel=corrgram::panel.fill, upper.panel=corrgram::panel.cor)
d3.mlt <- melt(select(d, record_id, group, cvlt_ldelay_recall_zscore, wb_clustering_x:fpn_betweenness_x), id.vars=c('record_id', 'group', 'cvlt_ldelay_recall_zscore'))
ggplot(data = d3.mlt) +
ggtitle('BCT Metrics and CVLT Long Delay z-score') +
geom_point(aes(x = value, y = cvlt_ldelay_recall_zscore, group = group, color = group), size=0.5) +
#stat_smooth(aes(x = value, y = ds_backward_score, group = group, color = group), method = 'loess', se = FALSE, fullrange = FALSE) +
facet_wrap(~ variable, scales='free') +
theme_minimal() +
scale_color_manual(values = brewer.pal(8, "Paired")[7:8], name = 'Group', labels = c('Young Adults', 'Older Adults')) +
xlab(element_blank()) + ylab('CVLT') +
theme(axis.text.y = element_blank(), axis.text.x = element_blank())## Warning: Removed 1455 rows containing missing values (geom_point).
summary(lm(dmn_modularity_x ~ group * IS, data = d))##
## Call:
## lm(formula = dmn_modularity_x ~ group * IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.112104 -0.038123 0.001876 0.035323 0.146968
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.36208 0.03654 9.908 5.86e-15 ***
## group1 -0.05246 0.04968 -1.056 0.295
## IS -0.02885 0.08894 -0.324 0.747
## group1:IS 0.06033 0.11218 0.538 0.592
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05738 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.05577, Adjusted R-squared: 0.0153
## F-statistic: 1.378 on 3 and 70 DF, p-value: 0.2566summary(lm(dmn_efficiency_x ~ group * IS, data = d))##
## Call:
## lm(formula = dmn_efficiency_x ~ group * IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.7431 -0.2053 -0.0256 0.2124 1.0236
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.1774 0.2218 14.324 <2e-16 ***
## group1 -0.5075 0.3016 -1.683 0.0969 .
## IS 0.2479 0.5399 0.459 0.6476
## group1:IS 0.2004 0.6809 0.294 0.7694
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3483 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.2633, Adjusted R-squared: 0.2317
## F-statistic: 8.34 on 3 and 70 DF, p-value: 8.135e-05summary(lm(dmn_clustering_x ~ group * IS, data = d))##
## Call:
## lm(formula = dmn_clustering_x ~ group * IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.062003 -0.021856 -0.003238 0.019953 0.074253
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.27165 0.01870 14.526 <2e-16 ***
## group1 0.02612 0.02542 1.028 0.308
## IS 0.05895 0.04551 1.295 0.200
## group1:IS -0.07742 0.05740 -1.349 0.182
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02936 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.03757, Adjusted R-squared: -0.003675
## F-statistic: 0.9109 on 3 and 70 DF, p-value: 0.4403summary(lm(dmn_participation_x ~ group * IS, data = d))##
## Call:
## lm(formula = dmn_participation_x ~ group * IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.183718 -0.037915 0.002937 0.045423 0.152378
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.45341 0.04250 10.668 2.54e-16 ***
## group1 -0.06873 0.05779 -1.189 0.238
## IS 0.07242 0.10345 0.700 0.486
## group1:IS 0.09696 0.13047 0.743 0.460
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06674 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.083, Adjusted R-squared: 0.0437
## F-statistic: 2.112 on 3 and 70 DF, p-value: 0.1065summary(lm(dmn_modularity_x ~ group + IS, data = d))##
## Call:
## lm(formula = dmn_modularity_x ~ group + IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.109905 -0.039188 0.001182 0.034580 0.143812
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.346982 0.023285 14.902 <2e-16 ***
## group1 -0.026814 0.013886 -1.931 0.0575 .
## IS 0.009077 0.053929 0.168 0.8668
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0571 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.05187, Adjusted R-squared: 0.02516
## F-statistic: 1.942 on 2 and 71 DF, p-value: 0.1509summary(lm(dmn_efficiency_x ~ group + IS, data = d))##
## Call:
## lm(formula = dmn_efficiency_x ~ group + IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.73703 -0.20557 -0.01522 0.22092 1.01080
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.12728 0.14114 22.158 < 2e-16 ***
## group1 -0.42231 0.08417 -5.017 3.73e-06 ***
## IS 0.37389 0.32688 1.144 0.257
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3461 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.2624, Adjusted R-squared: 0.2416
## F-statistic: 12.63 on 2 and 71 DF, p-value: 2.031e-05summary(lm(dmn_clustering_x ~ group + IS, data = d))##
## Call:
## lm(formula = dmn_clustering_x ~ group + IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.064339 -0.022741 -0.002518 0.019037 0.076297
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.291018 0.012044 24.162 <2e-16 ***
## group1 -0.006785 0.007183 -0.945 0.348
## IS 0.010279 0.027895 0.368 0.714
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02953 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.01256, Adjusted R-squared: -0.01525
## F-statistic: 0.4517 on 2 and 71 DF, p-value: 0.6384summary(lm(dmn_participation_x ~ group + IS, data = d)) # *##
## Call:
## lm(formula = dmn_participation_x ~ group + IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.180793 -0.038800 0.007265 0.049041 0.144545
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.42915 0.02713 15.817 <2e-16 ***
## group1 -0.02752 0.01618 -1.701 0.0934 .
## IS 0.13338 0.06284 2.122 0.0373 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06653 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.07576, Adjusted R-squared: 0.04973
## F-statistic: 2.91 on 2 and 71 DF, p-value: 0.061#---------------------------------------------------------
summary(lm(dmn_modularity_x ~ group * IV, data = d))##
## Call:
## lm(formula = dmn_modularity_x ~ group * IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.122659 -0.038845 -0.000611 0.035899 0.145679
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.30827 0.03493 8.824 5.55e-13 ***
## group1 0.03044 0.04882 0.623 0.535
## IV 0.04623 0.03688 1.254 0.214
## group1:IV -0.06281 0.05294 -1.186 0.239
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0568 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.07478, Adjusted R-squared: 0.03513
## F-statistic: 1.886 on 3 and 70 DF, p-value: 0.1399summary(lm(dmn_efficiency_x ~ group * IV, data = d))##
## Call:
## lm(formula = dmn_efficiency_x ~ group * IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.80823 -0.23404 -0.00458 0.22425 1.04151
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.4677 0.2116 16.389 <2e-16 ***
## group1 -0.2873 0.2957 -0.972 0.334
## IV -0.2093 0.2233 -0.937 0.352
## group1:IV -0.1386 0.3207 -0.432 0.667
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.344 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.2813, Adjusted R-squared: 0.2505
## F-statistic: 9.133 on 3 and 70 DF, p-value: 3.527e-05summary(lm(dmn_clustering_x ~ group * IV, data = d))##
## Call:
## lm(formula = dmn_clustering_x ~ group * IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.053654 -0.020411 -0.003014 0.019713 0.080206
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3171421 0.0179053 17.712 <2e-16 ***
## group1 -0.0070203 0.0250216 -0.281 0.780
## IV -0.0240665 0.0189005 -1.273 0.207
## group1:IV -0.0003998 0.0271348 -0.015 0.988
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02911 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.05393, Adjusted R-squared: 0.01339
## F-statistic: 1.33 on 3 and 70 DF, p-value: 0.2715summary(lm(dmn_participation_x ~ group * IV, data = d))##
## Call:
## lm(formula = dmn_participation_x ~ group * IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.189670 -0.038737 0.004867 0.048461 0.132920
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.471943 0.042475 11.111 <2e-16 ***
## group1 -0.010548 0.059356 -0.178 0.859
## IV 0.011244 0.044835 0.251 0.803
## group1:IV -0.007706 0.064369 -0.120 0.905
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06906 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.01809, Adjusted R-squared: -0.024
## F-statistic: 0.4298 on 3 and 70 DF, p-value: 0.7323summary(lm(dmn_modularity_x ~ group + IV, data = d))##
## Call:
## lm(formula = dmn_modularity_x ~ group + IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.114598 -0.037195 0.002641 0.035811 0.148695
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.33617 0.02591 12.975 <2e-16 ***
## group1 -0.02528 0.01337 -1.891 0.0627 .
## IV 0.01575 0.02654 0.594 0.5546
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05697 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.05618, Adjusted R-squared: 0.02959
## F-statistic: 2.113 on 2 and 71 DF, p-value: 0.1284summary(lm(dmn_efficiency_x ~ group + IV, data = d)) ###
## Call:
## lm(formula = dmn_efficiency_x ~ group + IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.77395 -0.23134 0.00052 0.21991 1.03912
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.52929 0.15558 22.685 < 2e-16 ***
## group1 -0.41033 0.08028 -5.112 2.59e-06 ***
## IV -0.27657 0.15934 -1.736 0.0869 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3421 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.2794, Adjusted R-squared: 0.2591
## F-statistic: 13.76 on 2 and 71 DF, p-value: 8.881e-06summary(lm(dmn_clustering_x ~ group + IV, data = d)) ###
## Call:
## lm(formula = dmn_clustering_x ~ group + IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.05356 -0.02046 -0.00302 0.01959 0.08023
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.317320 0.013148 24.135 <2e-16 ***
## group1 -0.007375 0.006784 -1.087 0.2807
## IV -0.024260 0.013466 -1.802 0.0758 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02891 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.05393, Adjusted R-squared: 0.02728
## F-statistic: 2.024 on 2 and 71 DF, p-value: 0.1397summary(lm(dmn_participation_x ~ group + IV, data = d))##
## Call:
## lm(formula = dmn_participation_x ~ group + IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.191375 -0.037965 0.005543 0.047914 0.134656
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.475366 0.031192 15.240 <2e-16 ***
## group1 -0.017383 0.016095 -1.080 0.284
## IV 0.007506 0.031946 0.235 0.815
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06858 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.01788, Adjusted R-squared: -0.009781
## F-statistic: 0.6464 on 2 and 71 DF, p-value: 0.527#---------------------------------------------------------
summary(lm(dmn_modularity_x ~ group * RA, data = d))##
## Call:
## lm(formula = dmn_modularity_x ~ group * RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.111575 -0.037934 -0.003595 0.033827 0.151931
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.344486 0.051472 6.693 4.52e-09 ***
## group1 0.036302 0.076770 0.473 0.638
## RA 0.007274 0.060345 0.121 0.904
## group1:RA -0.074565 0.090176 -0.827 0.411
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0571 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.06515, Adjusted R-squared: 0.02509
## F-statistic: 1.626 on 3 and 70 DF, p-value: 0.1911summary(lm(dmn_efficiency_x ~ group * RA, data = d))##
## Call:
## lm(formula = dmn_efficiency_x ~ group * RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.76111 -0.19850 -0.02646 0.22946 1.06958
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.44902 0.31613 10.910 <2e-16 ***
## group1 -0.45242 0.47150 -0.960 0.341
## RA -0.20593 0.37062 -0.556 0.580
## group1:RA 0.06791 0.55384 0.123 0.903
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3507 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.2533, Adjusted R-squared: 0.2213
## F-statistic: 7.915 on 3 and 70 DF, p-value: 0.0001282summary(lm(dmn_clustering_x ~ group * RA, data = d))##
## Call:
## lm(formula = dmn_clustering_x ~ group * RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.065233 -0.022471 -0.001541 0.019663 0.076597
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.306413 0.026781 11.441 <2e-16 ***
## group1 -0.007264 0.039943 -0.182 0.856
## RA -0.013461 0.031397 -0.429 0.669
## group1:RA 0.001428 0.046918 0.030 0.976
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02971 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.01494, Adjusted R-squared: -0.02728
## F-statistic: 0.3538 on 3 and 70 DF, p-value: 0.7865summary(lm(dmn_participation_x ~ group * RA, data = d)) # **##
## Call:
## lm(formula = dmn_participation_x ~ group * RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.181254 -0.041710 0.005337 0.043609 0.139249
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.45101 0.05535 8.148 9.77e-12 ***
## group1 -0.24477 0.08256 -2.965 0.00414 **
## RA 0.03719 0.06490 0.573 0.56848
## group1:RA 0.27117 0.09698 2.796 0.00667 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06141 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.2238, Adjusted R-squared: 0.1905
## F-statistic: 6.727 on 3 and 70 DF, p-value: 0.0004709summary(lm(dmn_modularity_x ~ group + RA, data = d))##
## Call:
## lm(formula = dmn_modularity_x ~ group + RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.109486 -0.038923 0.001191 0.033243 0.148117
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.37253 0.03864 9.642 1.55e-14 ***
## group1 -0.02621 0.01329 -1.973 0.0524 .
## RA -0.02612 0.04474 -0.584 0.5613
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05697 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.05602, Adjusted R-squared: 0.02943
## F-statistic: 2.107 on 2 and 71 DF, p-value: 0.1292summary(lm(dmn_efficiency_x ~ group + RA, data = d))##
## Call:
## lm(formula = dmn_efficiency_x ~ group + RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.76020 -0.19975 -0.02175 0.23637 1.06653
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.42348 0.23617 14.496 < 2e-16 ***
## group1 -0.39548 0.08123 -4.868 6.58e-06 ***
## RA -0.17552 0.27349 -0.642 0.523
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3482 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.2531, Adjusted R-squared: 0.2321
## F-statistic: 12.03 on 2 and 71 DF, p-value: 3.163e-05summary(lm(dmn_clustering_x ~ group + RA, data = d))##
## Call:
## lm(formula = dmn_clustering_x ~ group + RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.065214 -0.022464 -0.001523 0.019681 0.076604
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.305876 0.020005 15.290 <2e-16 ***
## group1 -0.006066 0.006881 -0.882 0.381
## RA -0.012822 0.023166 -0.553 0.582
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0295 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.01493, Adjusted R-squared: -0.01282
## F-statistic: 0.5379 on 2 and 71 DF, p-value: 0.5863#---------------------------------------------------------
summary(lm(dmn_modularity_x ~ group * fact, data = d))##
## Call:
## lm(formula = dmn_modularity_x ~ group * fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.104574 -0.042681 0.002067 0.038124 0.156193
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.669e-01 2.221e-02 16.515 <2e-16 ***
## group1 -6.133e-02 3.186e-02 -1.925 0.0583 .
## fact -3.996e-06 4.992e-06 -0.800 0.4262
## group1:fact 8.813e-06 6.834e-06 1.290 0.2015
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05644 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.06649, Adjusted R-squared: 0.02591
## F-statistic: 1.638 on 3 and 69 DF, p-value: 0.1885summary(lm(dmn_efficiency_x ~ group * fact, data = d)) # *##
## Call:
## lm(formula = dmn_efficiency_x ~ group * fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.79630 -0.17767 -0.05797 0.19886 1.11169
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.395e+00 1.306e-01 25.996 < 2e-16 ***
## group1 -8.170e-01 1.873e-01 -4.362 4.42e-05 ***
## fact -2.929e-05 2.935e-05 -0.998 0.3217
## group1:fact 1.009e-04 4.018e-05 2.510 0.0144 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3318 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.3148, Adjusted R-squared: 0.285
## F-statistic: 10.57 on 3 and 69 DF, p-value: 8.37e-06summary(lm(dmn_clustering_x ~ group * fact, data = d))##
## Call:
## lm(formula = dmn_clustering_x ~ group * fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.062777 -0.021476 -0.003239 0.021375 0.078796
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.892e-01 1.160e-02 24.939 <2e-16 ***
## group1 -1.603e-02 1.663e-02 -0.964 0.338
## fact 1.457e-06 2.605e-06 0.559 0.578
## group1:fact 2.149e-06 3.567e-06 0.602 0.549
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02946 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.04518, Adjusted R-squared: 0.003662
## F-statistic: 1.088 on 3 and 69 DF, p-value: 0.36summary(lm(dmn_participation_x ~ group * fact, data = d)) # *##
## Call:
## lm(formula = dmn_participation_x ~ group * fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.192262 -0.044581 0.005732 0.045846 0.131849
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.004e-01 2.590e-02 19.324 <2e-16 ***
## group1 -9.253e-02 3.714e-02 -2.492 0.0151 *
## fact -4.461e-06 5.819e-06 -0.767 0.4459
## group1:fact 1.654e-05 7.967e-06 2.076 0.0416 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06579 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.09638, Adjusted R-squared: 0.05709
## F-statistic: 2.453 on 3 and 69 DF, p-value: 0.07056summary(lm(dmn_modularity_x ~ group + fact, data = d))##
## Call:
## lm(formula = dmn_modularity_x ~ group + fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.111465 -0.036796 0.005418 0.034051 0.142505
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.477e-01 1.659e-02 20.957 <2e-16 ***
## group1 -2.402e-02 1.339e-02 -1.794 0.0771 .
## fact 7.057e-07 3.426e-06 0.206 0.8374
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0567 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.044, Adjusted R-squared: 0.01668
## F-statistic: 1.611 on 2 and 70 DF, p-value: 0.2071summary(lm(dmn_clustering_x ~ group + fact, data = d))##
## Call:
## lm(formula = dmn_clustering_x ~ group + fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.061159 -0.021287 -0.002668 0.023603 0.080422
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.845e-01 8.580e-03 33.158 <2e-16 ***
## group1 -6.929e-03 6.922e-03 -1.001 0.320
## fact 2.604e-06 1.771e-06 1.470 0.146
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02932 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.04015, Adjusted R-squared: 0.01273
## F-statistic: 1.464 on 2 and 70 DF, p-value: 0.2383#---------------------------------------------------------
summary(lm(dmn_modularity_x ~ group * actamp, data = d))##
## Call:
## lm(formula = dmn_modularity_x ~ group * actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.116078 -0.040402 0.005576 0.031654 0.148714
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.39803 0.06091 6.535 9.17e-09 ***
## group1 -0.04426 0.08158 -0.543 0.589
## actamp -0.03034 0.03853 -0.787 0.434
## group1:actamp 0.01251 0.05225 0.239 0.812
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05677 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.0554, Adjusted R-squared: 0.01433
## F-statistic: 1.349 on 3 and 69 DF, p-value: 0.2658summary(lm(dmn_efficiency_x ~ group * actamp, data = d))##
## Call:
## lm(formula = dmn_efficiency_x ~ group * actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.80199 -0.20771 -0.01272 0.21313 1.07048
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.3762 0.3692 9.146 1.62e-13 ***
## group1 -0.9770 0.4944 -1.976 0.0522 .
## actamp -0.0640 0.2335 -0.274 0.7848
## group1:actamp 0.3916 0.3167 1.237 0.2204
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3441 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.2633, Adjusted R-squared: 0.2312
## F-statistic: 8.219 on 3 and 69 DF, p-value: 9.434e-05summary(lm(dmn_clustering_x ~ group * actamp, data = d))##
## Call:
## lm(formula = dmn_clustering_x ~ group * actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.063632 -0.018714 -0.003235 0.018436 0.083204
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.233009 0.030543 7.629 9.53e-11 ***
## group1 0.007201 0.040907 0.176 0.8608
## actamp 0.039716 0.019320 2.056 0.0436 *
## group1:actamp -0.007399 0.026202 -0.282 0.7785
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02847 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.1082, Adjusted R-squared: 0.06946
## F-statistic: 2.791 on 3 and 69 DF, p-value: 0.04684summary(lm(dmn_participation_x ~ group * actamp, data = d)) # ##
## Call:
## lm(formula = dmn_participation_x ~ group * actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.172837 -0.044346 0.002105 0.039644 0.136660
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.55894 0.07070 7.905 2.98e-11 ***
## group1 -0.22254 0.09470 -2.350 0.0216 *
## actamp -0.04906 0.04473 -1.097 0.2765
## group1:actamp 0.13162 0.06066 2.170 0.0335 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0659 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.09334, Adjusted R-squared: 0.05392
## F-statistic: 2.368 on 3 and 69 DF, p-value: 0.07823summary(lm(dmn_modularity_x ~ group + actamp, data = d))##
## Call:
## lm(formula = dmn_modularity_x ~ group + actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.116987 -0.039542 0.002837 0.033169 0.150441
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.38740 0.04139 9.359 5.82e-14 ***
## group1 -0.02500 0.01333 -1.875 0.0649 .
## actamp -0.02354 0.02585 -0.910 0.3657
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05639 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.05461, Adjusted R-squared: 0.0276
## F-statistic: 2.022 on 2 and 70 DF, p-value: 0.1401summary(lm(dmn_efficiency_x ~ group + actamp, data = d))##
## Call:
## lm(formula = dmn_efficiency_x ~ group + actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.75048 -0.18510 -0.00085 0.24441 0.99880
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.04322 0.25353 12.003 < 2e-16 ***
## group1 -0.37385 0.08164 -4.579 1.97e-05 ***
## actamp 0.14893 0.15834 0.941 0.35
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3454 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.2469, Adjusted R-squared: 0.2254
## F-statistic: 11.48 on 2 and 70 DF, p-value: 4.888e-05summary(lm(dmn_clustering_x ~ group + actamp, data = d)) # **##
## Call:
## lm(formula = dmn_clustering_x ~ group + actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.063754 -0.018802 -0.004377 0.020229 0.082548
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.239299 0.020759 11.527 < 2e-16 ***
## group1 -0.004193 0.006684 -0.627 0.53249
## actamp 0.035694 0.012965 2.753 0.00751 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02828 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.1072, Adjusted R-squared: 0.08169
## F-statistic: 4.203 on 2 and 70 DF, p-value: 0.0189#---------------------------------------------------------
summary(lm(dmn_modularity_x ~ group * actphi, data = d))##
## Call:
## lm(formula = dmn_modularity_x ~ group * actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.109958 -0.037680 -0.005094 0.033524 0.151591
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3440711 0.1007758 3.414 0.00107 **
## group1 0.1523493 0.1402975 1.086 0.28130
## actphi 0.0003975 0.0061179 0.065 0.94838
## group1:actphi -0.0117903 0.0089439 -1.318 0.19178
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05591 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.08396, Adjusted R-squared: 0.04413
## F-statistic: 2.108 on 3 and 69 DF, p-value: 0.1071summary(lm(dmn_efficiency_x ~ group * actphi, data = d))##
## Call:
## lm(formula = dmn_efficiency_x ~ group * actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.73699 -0.20639 -0.00919 0.22304 1.04486
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.395275 0.628212 5.405 8.74e-07 ***
## group1 -0.038780 0.874581 -0.044 0.965
## actphi -0.007264 0.038138 -0.190 0.850
## group1:actphi -0.023769 0.055754 -0.426 0.671
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3485 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.2442, Adjusted R-squared: 0.2113
## F-statistic: 7.431 on 3 and 69 DF, p-value: 0.0002202summary(lm(dmn_clustering_x ~ group * actphi, data = d))##
## Call:
## lm(formula = dmn_clustering_x ~ group * actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.064725 -0.024070 -0.002608 0.016080 0.076650
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.958e-01 5.387e-02 5.491 6.22e-07 ***
## group1 -4.250e-02 7.499e-02 -0.567 0.573
## actphi -4.328e-05 3.270e-03 -0.013 0.989
## group1:actphi 2.444e-03 4.781e-03 0.511 0.611
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02988 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.01728, Adjusted R-squared: -0.02544
## F-statistic: 0.4045 on 3 and 69 DF, p-value: 0.7502summary(lm(dmn_participation_x ~ group * actphi, data = d))##
## Call:
## lm(formula = dmn_participation_x ~ group * actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.184131 -0.046960 0.005961 0.046840 0.143427
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.517250 0.120893 4.279 5.94e-05 ***
## group1 -0.244626 0.168304 -1.453 0.151
## actphi -0.002134 0.007339 -0.291 0.772
## group1:actphi 0.014802 0.010729 1.380 0.172
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06707 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.06099, Adjusted R-squared: 0.02016
## F-statistic: 1.494 on 3 and 69 DF, p-value: 0.2239summary(lm(dmn_modularity_x ~ group + actphi, data = d))##
## Call:
## lm(formula = dmn_modularity_x ~ group + actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.116517 -0.035314 -0.003438 0.036331 0.147037
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.434594 0.074147 5.861 1.37e-07 ***
## group1 -0.031566 0.014876 -2.122 0.0374 *
## actphi -0.005119 0.004486 -1.141 0.2577
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0562 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.06089, Adjusted R-squared: 0.03405
## F-statistic: 2.269 on 2 and 70 DF, p-value: 0.111summary(lm(dmn_efficiency_x ~ group + actphi, data = d))##
## Call:
## lm(formula = dmn_efficiency_x ~ group + actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.70945 -0.21270 -0.00609 0.22153 1.03863
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.57776 0.45710 7.827 3.80e-11 ***
## group1 -0.40955 0.09171 -4.466 2.99e-05 ***
## actphi -0.01839 0.02766 -0.665 0.508
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3465 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.2422, Adjusted R-squared: 0.2206
## F-statistic: 11.19 on 2 and 70 DF, p-value: 6.086e-05summary(lm(dmn_clustering_x ~ group + actphi, data = d))##
## Call:
## lm(formula = dmn_clustering_x ~ group + actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.067558 -0.024533 -0.002747 0.017797 0.078722
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.277053 0.039219 7.064 9.53e-10 ***
## group1 -0.004368 0.007868 -0.555 0.581
## actphi 0.001100 0.002373 0.464 0.644
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02973 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.01356, Adjusted R-squared: -0.01462
## F-statistic: 0.4812 on 2 and 70 DF, p-value: 0.6201summary(lm(dmn_participation_x ~ group + actphi, data = d))##
## Call:
## lm(formula = dmn_participation_x ~ group + actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.194075 -0.041461 0.001791 0.054278 0.126275
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.403605 0.089052 4.532 2.35e-05 ***
## group1 -0.013732 0.017866 -0.769 0.445
## actphi 0.004792 0.005388 0.889 0.377
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0675 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.03509, Adjusted R-squared: 0.007518
## F-statistic: 1.273 on 2 and 70 DF, p-value: 0.2865#---------------------------------------------------------
summary(lm(dmn_modularity_x ~ group * sleep_time, data = d))##
## Call:
## lm(formula = dmn_modularity_x ~ group * sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.108462 -0.040859 0.000418 0.033036 0.148570
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2425486 0.0607980 3.989 0.000159 ***
## group1 0.1008379 0.0816104 1.236 0.220679
## sleep_time 0.0003288 0.0001831 1.796 0.076690 .
## group1:sleep_time -0.0003868 0.0002377 -1.627 0.108176
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05613 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.1003, Adjusted R-squared: 0.06225
## F-statistic: 2.637 on 3 and 71 DF, p-value: 0.0562summary(lm(dmn_efficiency_x ~ group * sleep_time, data = d))##
## Call:
## lm(formula = dmn_efficiency_x ~ group * sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.74259 -0.20371 -0.02172 0.21182 0.99417
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.638247 0.375792 9.682 1.31e-14 ***
## group1 -0.798817 0.504433 -1.584 0.118
## sleep_time -0.001102 0.001131 -0.974 0.333
## group1:sleep_time 0.001216 0.001469 0.828 0.411
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3469 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.263, Adjusted R-squared: 0.2318
## F-statistic: 8.444 on 3 and 71 DF, p-value: 7.141e-05summary(lm(dmn_clustering_x ~ group * sleep_time, data = d))##
## Call:
## lm(formula = dmn_clustering_x ~ group * sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.063239 -0.023123 -0.000635 0.018605 0.078777
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.417e-01 3.150e-02 10.847 <2e-16 ***
## group1 -4.293e-02 4.229e-02 -1.015 0.313
## sleep_time -1.418e-04 9.485e-05 -1.495 0.139
## group1:sleep_time 1.145e-04 1.232e-04 0.930 0.356
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02908 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.04245, Adjusted R-squared: 0.001988
## F-statistic: 1.049 on 3 and 71 DF, p-value: 0.3763summary(lm(dmn_participation_x ~ group * sleep_time, data = d))##
## Call:
## lm(formula = dmn_participation_x ~ group * sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.170259 -0.039553 0.005276 0.041173 0.135262
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.980e-01 7.247e-02 5.493 5.82e-07 ***
## group1 -4.829e-02 9.727e-02 -0.496 0.621
## sleep_time 2.563e-04 2.182e-04 1.175 0.244
## group1:sleep_time 7.382e-05 2.833e-04 0.261 0.795
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0669 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.07502, Adjusted R-squared: 0.03594
## F-statistic: 1.92 on 3 and 71 DF, p-value: 0.1342summary(lm(dmn_modularity_x ~ group + sleep_time, data = d))##
## Call:
## lm(formula = dmn_modularity_x ~ group + sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.115869 -0.038203 0.000163 0.035072 0.152369
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.179e-01 3.983e-02 7.981 1.66e-11 ***
## group1 -3.016e-02 1.347e-02 -2.240 0.0282 *
## sleep_time 9.949e-05 1.181e-04 0.842 0.4024
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05677 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.06672, Adjusted R-squared: 0.0408
## F-statistic: 2.574 on 2 and 72 DF, p-value: 0.08325summary(lm(dmn_efficiency_x ~ group + sleep_time, data = d))##
## Call:
## lm(formula = dmn_efficiency_x ~ group + sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.75070 -0.20422 -0.00207 0.23490 1.02702
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.4012965 0.2429005 14.003 < 2e-16 ***
## group1 -0.3869065 0.0821132 -4.712 1.16e-05 ***
## sleep_time -0.0003811 0.0007203 -0.529 0.598
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3462 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.2559, Adjusted R-squared: 0.2352
## F-statistic: 12.38 on 2 and 72 DF, p-value: 2.397e-05summary(lm(dmn_clustering_x ~ group + sleep_time, data = d))##
## Call:
## lm(formula = dmn_clustering_x ~ group + sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.06400 -0.02197 -0.00142 0.01926 0.07780
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.194e-01 2.039e-02 15.666 <2e-16 ***
## group1 -4.145e-03 6.892e-03 -0.601 0.549
## sleep_time -7.391e-05 6.045e-05 -1.223 0.225
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02906 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.03079, Adjusted R-squared: 0.003866
## F-statistic: 1.144 on 2 and 72 DF, p-value: 0.3244summary(lm(dmn_participation_x ~ group + sleep_time, data = d)) # *##
## Call:
## lm(formula = dmn_participation_x ~ group + sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.172068 -0.038697 0.005079 0.040363 0.137369
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3836351 0.0466374 8.226 5.81e-12 ***
## group1 -0.0232918 0.0157659 -1.477 0.1439
## sleep_time 0.0003001 0.0001383 2.170 0.0333 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06647 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.07414, Adjusted R-squared: 0.04842
## F-statistic: 2.883 on 2 and 72 DF, p-value: 0.06247#---------------------------------------------------------
summary(lm(dmn_modularity_x ~ group * efficiency, data = d))##
## Call:
## lm(formula = dmn_modularity_x ~ group * efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.111625 -0.039788 0.000747 0.033809 0.154515
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3342463 0.1057566 3.161 0.00232 **
## group1 -0.0855977 0.1450541 -0.590 0.55699
## efficiency 0.0002279 0.0014692 0.155 0.87714
## group1:efficiency 0.0008010 0.0020081 0.399 0.69119
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05721 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.06528, Adjusted R-squared: 0.02578
## F-statistic: 1.653 on 3 and 71 DF, p-value: 0.185summary(lm(dmn_efficiency_x ~ group * efficiency, data = d))##
## Call:
## lm(formula = dmn_efficiency_x ~ group * efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.74316 -0.21623 -0.03005 0.13530 1.11008
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.21782 0.63486 6.644 5.25e-09 ***
## group1 -1.61726 0.87076 -1.857 0.0674 .
## efficiency -0.01313 0.00882 -1.489 0.1410
## group1:efficiency 0.01700 0.01205 1.410 0.1629
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3434 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.2778, Adjusted R-squared: 0.2472
## F-statistic: 9.102 on 3 and 71 DF, p-value: 3.564e-05summary(lm(dmn_clustering_x ~ group * efficiency, data = d))##
## Call:
## lm(formula = dmn_clustering_x ~ group * efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.064250 -0.022226 -0.001156 0.018199 0.074228
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3415037 0.0543525 6.283 2.35e-08 ***
## group1 -0.0428591 0.0745490 -0.575 0.567
## efficiency -0.0006469 0.0007551 -0.857 0.394
## group1:efficiency 0.0005150 0.0010320 0.499 0.619
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0294 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.02127, Adjusted R-squared: -0.02008
## F-statistic: 0.5144 on 3 and 71 DF, p-value: 0.6737summary(lm(dmn_participation_x ~ group * efficiency, data = d))##
## Call:
## lm(formula = dmn_participation_x ~ group * efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.187120 -0.046843 0.007178 0.046813 0.138189
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.860e-01 1.234e-01 3.939 0.000189 ***
## group1 -2.798e-01 1.692e-01 -1.654 0.102634
## efficiency -5.202e-05 1.714e-03 -0.030 0.975868
## group1:efficiency 3.657e-03 2.342e-03 1.561 0.122862
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06673 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.07968, Adjusted R-squared: 0.04079
## F-statistic: 2.049 on 3 and 71 DF, p-value: 0.1147summary(lm(dmn_modularity_x ~ group + efficiency, data = d))##
## Call:
## lm(formula = dmn_modularity_x ~ group + efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.113871 -0.039754 0.000017 0.034424 0.150733
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3034970 0.0719736 4.217 7.1e-05 ***
## group1 -0.0279818 0.0131724 -2.124 0.0371 *
## efficiency 0.0006567 0.0009957 0.660 0.5117
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05688 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.06319, Adjusted R-squared: 0.03716
## F-statistic: 2.428 on 2 and 72 DF, p-value: 0.0954summary(lm(dmn_efficiency_x ~ group + efficiency, data = d))##
## Call:
## lm(formula = dmn_efficiency_x ~ group + efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.75135 -0.19980 -0.02557 0.20939 1.06771
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.565273 0.437577 8.148 8.12e-12 ***
## group1 -0.394555 0.080084 -4.927 5.16e-06 ***
## efficiency -0.004032 0.006053 -0.666 0.507
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3458 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.2575, Adjusted R-squared: 0.2369
## F-statistic: 12.49 on 2 and 72 DF, p-value: 2.21e-05summary(lm(dmn_clustering_x ~ group + efficiency, data = d))##
## Call:
## lm(formula = dmn_clustering_x ~ group + efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.064498 -0.022706 -0.000786 0.018243 0.075293
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3217344 0.0370134 8.692 7.82e-13 ***
## group1 -0.0058167 0.0067741 -0.859 0.393
## efficiency -0.0003712 0.0005120 -0.725 0.471
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02925 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.01784, Adjusted R-squared: -0.009443
## F-statistic: 0.6539 on 2 and 72 DF, p-value: 0.5231summary(lm(dmn_participation_x ~ group + efficiency, data = d))##
## Call:
## lm(formula = dmn_participation_x ~ group + efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.189923 -0.045773 0.006858 0.046630 0.136427
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.345559 0.085287 4.052 0.000127 ***
## group1 -0.016687 0.015609 -1.069 0.288623
## efficiency 0.001906 0.001180 1.615 0.110633
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0674 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.04808, Adjusted R-squared: 0.02164
## F-statistic: 1.818 on 2 and 72 DF, p-value: 0.1697#---------------------------------------------------------
summary(lm(dmn_modularity_x ~ group * total_ac, data = d)) ###
## Call:
## lm(formula = dmn_modularity_x ~ group * total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.111650 -0.038074 -0.009147 0.039101 0.148045
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.438e-01 2.194e-02 15.671 <2e-16 ***
## group1 -8.804e-02 3.883e-02 -2.267 0.0264 *
## total_ac 4.486e-08 1.336e-07 0.336 0.7379
## group1:total_ac 4.774e-07 2.733e-07 1.747 0.0850 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05556 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.1185, Adjusted R-squared: 0.08126
## F-statistic: 3.182 on 3 and 71 DF, p-value: 0.02906summary(lm(dmn_efficiency_x ~ group * total_ac, data = d))##
## Call:
## lm(formula = dmn_efficiency_x ~ group * total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.7231 -0.2102 0.0345 0.1944 1.0333
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.144e+00 1.347e-01 23.336 <2e-16 ***
## group1 -5.484e-01 2.385e-01 -2.300 0.0244 *
## total_ac 8.746e-07 8.202e-07 1.066 0.2899
## group1:total_ac 1.333e-06 1.678e-06 0.795 0.4295
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3412 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.2872, Adjusted R-squared: 0.2571
## F-statistic: 9.536 on 3 and 71 DF, p-value: 2.267e-05summary(lm(dmn_clustering_x ~ group * total_ac, data = d))##
## Call:
## lm(formula = dmn_clustering_x ~ group * total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.061514 -0.019534 -0.002643 0.015632 0.080344
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.814e-01 1.125e-02 25.017 <2e-16 ***
## group1 -2.256e-02 1.991e-02 -1.133 0.261
## total_ac 9.109e-08 6.847e-08 1.330 0.188
## group1:total_ac 1.446e-07 1.401e-07 1.032 0.305
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02848 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.08167, Adjusted R-squared: 0.04287
## F-statistic: 2.105 on 3 and 71 DF, p-value: 0.1072summary(lm(dmn_participation_x ~ group * total_ac, data = d))##
## Call:
## lm(formula = dmn_participation_x ~ group * total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.190218 -0.039904 0.003421 0.047881 0.141558
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.681e-01 2.703e-02 17.319 <2e-16 ***
## group1 3.650e-02 4.784e-02 0.763 0.448
## total_ac 9.373e-08 1.645e-07 0.570 0.571
## group1:total_ac -3.910e-07 3.366e-07 -1.161 0.249
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06844 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.03198, Adjusted R-squared: -0.008926
## F-statistic: 0.7818 on 3 and 71 DF, p-value: 0.508summary(lm(dmn_modularity_x ~ group + total_ac, data = d))##
## Call:
## lm(formula = dmn_modularity_x ~ group + total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.11475 -0.03987 -0.00162 0.03485 0.14747
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.267e-01 1.990e-02 16.419 <2e-16 ***
## group1 -2.418e-02 1.330e-02 -1.818 0.0732 .
## total_ac 1.589e-07 1.182e-07 1.345 0.1830
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.05635 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.08061, Adjusted R-squared: 0.05507
## F-statistic: 3.157 on 2 and 72 DF, p-value: 0.04852summary(lm(dmn_efficiency_x ~ group + total_ac, data = d)) ###
## Call:
## lm(formula = dmn_efficiency_x ~ group + total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.71151 -0.22305 -0.00039 0.15870 1.02764
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.096e+00 1.202e-01 25.768 < 2e-16 ***
## group1 -3.701e-01 8.032e-02 -4.608 1.72e-05 ***
## total_ac 1.193e-06 7.137e-07 1.672 0.0989 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3403 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.2809, Adjusted R-squared: 0.2609
## F-statistic: 14.06 on 2 and 72 DF, p-value: 7e-06summary(lm(dmn_clustering_x ~ group + total_ac, data = d)) # *##
## Call:
## lm(formula = dmn_clustering_x ~ group + total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.06026 -0.01865 -0.00243 0.01630 0.08172
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.762e-01 1.006e-02 27.450 <2e-16 ***
## group1 -3.217e-03 6.726e-03 -0.478 0.634
## total_ac 1.256e-07 5.976e-08 2.102 0.039 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.02849 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.06789, Adjusted R-squared: 0.042
## F-statistic: 2.622 on 2 and 72 DF, p-value: 0.07959summary(lm(dmn_participation_x ~ group + total_ac, data = d))##
## Call:
## lm(formula = dmn_participation_x ~ group + total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.19015 -0.03766 0.00310 0.04979 0.13816
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.822e-01 2.423e-02 19.904 <2e-16 ***
## group1 -1.580e-02 1.619e-02 -0.976 0.332
## total_ac 3.322e-10 1.439e-07 0.002 0.998
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06861 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.01358, Adjusted R-squared: -0.01382
## F-statistic: 0.4958 on 2 and 72 DF, p-value: 0.6112summary(lm(fpn_modularity_x ~ group * IS, data = d))##
## Call:
## lm(formula = fpn_modularity_x ~ group * IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.141839 -0.042182 0.005995 0.048093 0.114177
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.38298 0.04118 9.301 7.44e-14 ***
## group1 0.01343 0.05598 0.240 0.811
## IS 0.02188 0.10022 0.218 0.828
## group1:IS -0.05903 0.12640 -0.467 0.642
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06466 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.01404, Adjusted R-squared: -0.02822
## F-statistic: 0.3322 on 3 and 70 DF, p-value: 0.8021summary(lm(fpn_efficiency_x ~ group * IS, data = d))##
## Call:
## lm(formula = fpn_efficiency_x ~ group * IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.82652 -0.21188 -0.02649 0.19262 1.08523
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.74193 0.22679 12.090 <2e-16 ***
## group1 -0.05895 0.30834 -0.191 0.849
## IS 0.43196 0.55199 0.783 0.437
## group1:IS -0.24265 0.69618 -0.349 0.728
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3561 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.05049, Adjusted R-squared: 0.009798
## F-statistic: 1.241 on 3 and 70 DF, p-value: 0.3015summary(lm(fpn_clustering_x ~ group * IS, data = d))##
## Call:
## lm(formula = fpn_clustering_x ~ group * IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.073104 -0.021323 0.005808 0.019413 0.075319
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.31432 0.02074 15.156 <2e-16 ***
## group1 -0.01863 0.02820 -0.661 0.511
## IS -0.06880 0.05048 -1.363 0.177
## group1:IS 0.06562 0.06366 1.031 0.306
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03257 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.03817, Adjusted R-squared: -0.003051
## F-statistic: 0.926 on 3 and 70 DF, p-value: 0.4329summary(lm(fpn_participation_x ~ group * IS, data = d))##
## Call:
## lm(formula = fpn_participation_x ~ group * IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.25782 -0.04083 0.02018 0.03950 0.13087
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.63874 0.04615 13.842 <2e-16 ***
## group1 -0.03754 0.06274 -0.598 0.551
## IS -0.11066 0.11231 -0.985 0.328
## group1:IS 0.16869 0.14165 1.191 0.238
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07246 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.07196, Adjusted R-squared: 0.03218
## F-statistic: 1.809 on 3 and 70 DF, p-value: 0.1534summary(lm(fpn_modularity_x ~ group + IS, data = d))##
## Call:
## lm(formula = fpn_modularity_x ~ group + IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.14204 -0.03888 0.00439 0.04814 0.11060
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.39774 0.02622 15.168 <2e-16 ***
## group1 -0.01166 0.01564 -0.745 0.459
## IS -0.01523 0.06073 -0.251 0.803
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0643 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.01097, Adjusted R-squared: -0.01689
## F-statistic: 0.3936 on 2 and 71 DF, p-value: 0.6761summary(lm(fpn_efficiency_x ~ group + IS, data = d))##
## Call:
## lm(formula = fpn_efficiency_x ~ group + IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.83384 -0.21432 -0.01508 0.18096 1.10079
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.80264 0.14433 19.418 <2e-16 ***
## group1 -0.16209 0.08608 -1.883 0.0638 .
## IS 0.27942 0.33428 0.836 0.4060
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3539 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.04884, Adjusted R-squared: 0.02205
## F-statistic: 1.823 on 2 and 71 DF, p-value: 0.169summary(lm(fpn_clustering_x ~ group + IS, data = d))##
## Call:
## lm(formula = fpn_clustering_x ~ group + IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.073613 -0.021925 0.006085 0.020493 0.075541
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.297896 0.013287 22.420 <2e-16 ***
## group1 0.009268 0.007924 1.170 0.246
## IS -0.027546 0.030773 -0.895 0.374
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03258 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.02357, Adjusted R-squared: -0.003935
## F-statistic: 0.857 on 2 and 71 DF, p-value: 0.4288summary(lm(fpn_participation_x ~ group + IS, data = d))##
## Call:
## lm(formula = fpn_participation_x ~ group + IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.25273 -0.03729 0.02368 0.04047 0.12111
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.596529 0.029638 20.127 <2e-16 ***
## group1 0.034162 0.017675 1.933 0.0573 .
## IS -0.004614 0.068643 -0.067 0.9466
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07267 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.05315, Adjusted R-squared: 0.02648
## F-statistic: 1.993 on 2 and 71 DF, p-value: 0.1438#---------------------------------------------------------
summary(lm(fpn_modularity_x ~ group * IV, data = d))##
## Call:
## lm(formula = fpn_modularity_x ~ group * IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.156812 -0.043619 0.009282 0.046264 0.108921
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.48198 0.03819 12.622 <2e-16 ***
## group1 -0.08616 0.05336 -1.615 0.1109
## IV -0.09863 0.04031 -2.447 0.0169 *
## group1:IV 0.07898 0.05787 1.365 0.1767
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06209 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.09077, Adjusted R-squared: 0.0518
## F-statistic: 2.329 on 3 and 70 DF, p-value: 0.08182summary(lm(fpn_efficiency_x ~ group * IV, data = d))##
## Call:
## lm(formula = fpn_efficiency_x ~ group * IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.8151 -0.1835 -0.0117 0.1843 1.1107
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.3941 0.2082 16.304 <2e-16 ***
## group1 -0.3029 0.2909 -1.041 0.3014
## IV -0.5246 0.2197 -2.387 0.0197 *
## group1:IV 0.1537 0.3155 0.487 0.6277
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3385 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.1422, Adjusted R-squared: 0.1055
## F-statistic: 3.869 on 3 and 70 DF, p-value: 0.01278summary(lm(fpn_clustering_x ~ group * IV, data = d))##
## Call:
## lm(formula = fpn_clustering_x ~ group * IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.073046 -0.019868 0.004755 0.018798 0.074764
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.29982 0.02003 14.969 <2e-16 ***
## group1 0.01667 0.02799 0.596 0.553
## IV -0.01408 0.02114 -0.666 0.508
## group1:IV -0.01184 0.03035 -0.390 0.698
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03257 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.0381, Adjusted R-squared: -0.003124
## F-statistic: 0.9242 on 3 and 70 DF, p-value: 0.4337summary(lm(fpn_participation_x ~ group * IV, data = d))##
## Call:
## lm(formula = fpn_participation_x ~ group * IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.25322 -0.03977 0.02444 0.04070 0.12295
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.54923 0.04466 12.299 <2e-16 ***
## group1 0.07364 0.06240 1.180 0.242
## IV 0.04965 0.04714 1.053 0.296
## group1:IV -0.04309 0.06767 -0.637 0.526
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07261 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.06811, Adjusted R-squared: 0.02817
## F-statistic: 1.705 on 3 and 70 DF, p-value: 0.1738summary(lm(fpn_modularity_x ~ group + IV, data = d)) # *##
## Call:
## lm(formula = fpn_modularity_x ~ group + IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.16210 -0.03644 0.01300 0.04502 0.09477
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.44690 0.02841 15.730 <2e-16 ***
## group1 -0.01610 0.01466 -1.098 0.2759
## IV -0.06031 0.02910 -2.073 0.0418 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06247 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.06657, Adjusted R-squared: 0.04028
## F-statistic: 2.532 on 2 and 71 DF, p-value: 0.08667summary(lm(fpn_efficiency_x ~ group + IV, data = d)) # **##
## Call:
## lm(formula = fpn_efficiency_x ~ group + IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.84122 -0.19704 -0.01341 0.17411 1.11331
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.32583 0.15312 21.721 < 2e-16 ***
## group1 -0.16657 0.07901 -2.108 0.03853 *
## IV -0.45001 0.15682 -2.870 0.00541 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3367 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.1393, Adjusted R-squared: 0.1151
## F-statistic: 5.746 on 2 and 71 DF, p-value: 0.004865summary(lm(fpn_clustering_x ~ group + IV, data = d))##
## Call:
## lm(formula = fpn_clustering_x ~ group + IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.073044 -0.017420 0.003783 0.019505 0.074887
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.305078 0.014723 20.721 <2e-16 ***
## group1 0.006166 0.007597 0.812 0.420
## IV -0.019820 0.015079 -1.314 0.193
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03237 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.03601, Adjusted R-squared: 0.008854
## F-statistic: 1.326 on 2 and 71 DF, p-value: 0.272summary(lm(fpn_participation_x ~ group + IV, data = d))##
## Call:
## lm(formula = fpn_participation_x ~ group + IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.25292 -0.03980 0.02399 0.04195 0.12200
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.56837 0.03289 17.283 <2e-16 ***
## group1 0.03541 0.01697 2.087 0.0405 *
## IV 0.02875 0.03368 0.854 0.3962
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07231 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.06271, Adjusted R-squared: 0.03631
## F-statistic: 2.375 on 2 and 71 DF, p-value: 0.1003#---------------------------------------------------------
summary(lm(fpn_modularity_x ~ group * RA, data = d))##
## Call:
## lm(formula = fpn_modularity_x ~ group * RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.141862 -0.033786 0.005158 0.044684 0.126704
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.46231 0.05764 8.021 1.67e-11 ***
## group1 -0.11933 0.08596 -1.388 0.169
## RA -0.08410 0.06757 -1.245 0.217
## group1:RA 0.12702 0.10097 1.258 0.213
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06393 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.03593, Adjusted R-squared: -0.005384
## F-statistic: 0.8697 on 3 and 70 DF, p-value: 0.461summary(lm(fpn_efficiency_x ~ group * RA, data = d))##
## Call:
## lm(formula = fpn_efficiency_x ~ group * RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.85033 -0.18945 -0.01325 0.13893 1.13963
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.0005 0.3160 9.496 3.28e-14 ***
## group1 0.3707 0.4713 0.787 0.434
## RA -0.1032 0.3704 -0.279 0.781
## group1:RA -0.6122 0.5536 -1.106 0.273
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3505 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.08025, Adjusted R-squared: 0.04083
## F-statistic: 2.036 on 3 and 70 DF, p-value: 0.1167summary(lm(fpn_clustering_x ~ group * RA, data = d))##
## Call:
## lm(formula = fpn_clustering_x ~ group * RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.071967 -0.019264 0.001985 0.021371 0.073050
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.36363 0.02792 13.026 < 2e-16 ***
## group1 -0.02984 0.04164 -0.717 0.47599
## RA -0.09133 0.03273 -2.791 0.00677 **
## group1:RA 0.04404 0.04891 0.901 0.37092
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03097 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.1303, Adjusted R-squared: 0.09308
## F-statistic: 3.497 on 3 and 70 DF, p-value: 0.01993summary(lm(fpn_participation_x ~ group * RA, data = d))##
## Call:
## lm(formula = fpn_participation_x ~ group * RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.24662 -0.03858 0.01895 0.04502 0.11589
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.56374 0.06495 8.680 1.02e-12 ***
## group1 -0.03573 0.09687 -0.369 0.713
## RA 0.03686 0.07614 0.484 0.630
## group1:RA 0.08317 0.11378 0.731 0.467
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07205 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.08258, Adjusted R-squared: 0.04326
## F-statistic: 2.1 on 3 and 70 DF, p-value: 0.108summary(lm(fpn_modularity_x ~ group + RA, data = d))##
## Call:
## lm(formula = fpn_modularity_x ~ group + RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.142377 -0.038324 0.006292 0.047144 0.112450
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.41454 0.04354 9.522 2.57e-14 ***
## group1 -0.01283 0.01498 -0.857 0.394
## RA -0.02722 0.05042 -0.540 0.591
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0642 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.01414, Adjusted R-squared: -0.01363
## F-statistic: 0.5091 on 2 and 71 DF, p-value: 0.6032summary(lm(fpn_efficiency_x ~ group + RA, data = d))##
## Call:
## lm(formula = fpn_efficiency_x ~ group + RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.85848 -0.18106 -0.02359 0.16609 1.16712
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.23073 0.23808 13.570 <2e-16 ***
## group1 -0.14263 0.08189 -1.742 0.0859 .
## RA -0.37735 0.27570 -1.369 0.1754
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3511 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.06418, Adjusted R-squared: 0.03781
## F-statistic: 2.434 on 2 and 71 DF, p-value: 0.09493summary(lm(fpn_clustering_x ~ group + RA, data = d)) # **##
## Call:
## lm(formula = fpn_clustering_x ~ group + RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.071416 -0.020194 0.004119 0.021199 0.071899
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.347068 0.020973 16.548 < 2e-16 ***
## group1 0.007089 0.007214 0.983 0.32912
## RA -0.071611 0.024287 -2.949 0.00432 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03093 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.1203, Adjusted R-squared: 0.09549
## F-statistic: 4.853 on 2 and 71 DF, p-value: 0.01058summary(lm(fpn_participation_x ~ group + RA, data = d))##
## Call:
## lm(formula = fpn_participation_x ~ group + RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.24067 -0.04059 0.02030 0.04786 0.11104
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.53246 0.04870 10.934 <2e-16 ***
## group1 0.03400 0.01675 2.030 0.0461 *
## RA 0.07410 0.05639 1.314 0.1931
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07181 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.07557, Adjusted R-squared: 0.04953
## F-statistic: 2.902 on 2 and 71 DF, p-value: 0.06144#---------------------------------------------------------
summary(lm(fpn_modularity_x ~ group * fact, data = d))##
## Call:
## lm(formula = fpn_modularity_x ~ group * fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.140671 -0.042290 0.004583 0.048751 0.110322
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.912e-01 2.541e-02 15.399 <2e-16 ***
## group1 -2.807e-02 3.643e-02 -0.770 0.444
## fact 1.129e-07 5.709e-06 0.020 0.984
## group1:fact 3.884e-06 7.816e-06 0.497 0.621
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06455 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.01534, Adjusted R-squared: -0.02748
## F-statistic: 0.3582 on 3 and 69 DF, p-value: 0.7833summary(lm(fpn_efficiency_x ~ group * fact, data = d))##
## Call:
## lm(formula = fpn_efficiency_x ~ group * fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.80302 -0.20754 -0.02366 0.18303 1.06211
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.786e+00 1.336e-01 20.846 <2e-16 ***
## group1 -1.879e-01 1.917e-01 -0.980 0.330
## fact 3.136e-05 3.003e-05 1.044 0.300
## group1:fact 1.330e-05 4.111e-05 0.324 0.747
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3395 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.07778, Adjusted R-squared: 0.03769
## F-statistic: 1.94 on 3 and 69 DF, p-value: 0.1312summary(lm(fpn_clustering_x ~ group * fact, data = d))##
## Call:
## lm(formula = fpn_clustering_x ~ group * fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.075338 -0.022109 0.003819 0.020138 0.072927
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.987e-01 1.269e-02 23.528 <2e-16 ***
## group1 -4.521e-04 1.821e-02 -0.025 0.980
## fact -2.883e-06 2.852e-06 -1.011 0.316
## group1:fact 2.360e-06 3.905e-06 0.604 0.548
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03225 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.03448, Adjusted R-squared: -0.007497
## F-statistic: 0.8214 on 3 and 69 DF, p-value: 0.4865summary(lm(fpn_participation_x ~ group * fact, data = d))##
## Call:
## lm(formula = fpn_participation_x ~ group * fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.25744 -0.03448 0.02448 0.04028 0.13706
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.124e-01 2.884e-02 21.233 <2e-16 ***
## group1 1.909e-03 4.136e-02 0.046 0.963
## fact -4.349e-06 6.481e-06 -0.671 0.504
## group1:fact 7.374e-06 8.873e-06 0.831 0.409
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07328 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.0595, Adjusted R-squared: 0.01861
## F-statistic: 1.455 on 3 and 69 DF, p-value: 0.2344summary(lm(fpn_modularity_x ~ group + fact, data = d))##
## Call:
## lm(formula = fpn_modularity_x ~ group + fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.142210 -0.046122 0.006569 0.048626 0.111343
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.828e-01 1.878e-02 20.377 <2e-16 ***
## group1 -1.162e-02 1.515e-02 -0.767 0.446
## fact 2.185e-06 3.878e-06 0.563 0.575
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0642 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.01181, Adjusted R-squared: -0.01642
## F-statistic: 0.4183 on 2 and 70 DF, p-value: 0.6598summary(lm(fpn_efficiency_x ~ group + fact, data = d))##
## Call:
## lm(formula = fpn_efficiency_x ~ group + fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.79300 -0.21844 -0.02739 0.18397 1.04691
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.757e+00 9.871e-02 27.931 <2e-16 ***
## group1 -1.315e-01 7.964e-02 -1.651 0.1031
## fact 3.845e-05 2.038e-05 1.887 0.0633 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3374 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.07638, Adjusted R-squared: 0.04999
## F-statistic: 2.895 on 2 and 70 DF, p-value: 0.06197summary(lm(fpn_clustering_x ~ group + fact, data = d))##
## Call:
## lm(formula = fpn_clustering_x ~ group + fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.076545 -0.023179 0.005353 0.020567 0.071588
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.936e-01 9.394e-03 31.249 <2e-16 ***
## group1 9.539e-03 7.579e-03 1.259 0.212
## fact -1.624e-06 1.939e-06 -0.838 0.405
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0321 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.02937, Adjusted R-squared: 0.001642
## F-statistic: 1.059 on 2 and 70 DF, p-value: 0.3522summary(lm(fpn_participation_x ~ group + fact, data = d))##
## Call:
## lm(formula = fpn_participation_x ~ group + fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.25298 -0.03741 0.02388 0.04105 0.12225
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.964e-01 2.139e-02 27.877 <2e-16 ***
## group1 3.313e-02 1.726e-02 1.920 0.059 .
## fact -4.149e-07 4.417e-06 -0.094 0.925
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07311 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.05009, Adjusted R-squared: 0.02295
## F-statistic: 1.845 on 2 and 70 DF, p-value: 0.1656#---------------------------------------------------------
summary(lm(fpn_modularity_x ~ group * actamp, data = d))##
## Call:
## lm(formula = fpn_modularity_x ~ group * actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.143840 -0.039318 0.005595 0.043191 0.109942
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.378005 0.069506 5.438 7.66e-07 ***
## group1 -0.002629 0.093094 -0.028 0.978
## actamp 0.008749 0.043967 0.199 0.843
## group1:actamp -0.005157 0.059629 -0.086 0.931
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06479 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.008013, Adjusted R-squared: -0.03512
## F-statistic: 0.1858 on 3 and 69 DF, p-value: 0.9057summary(lm(fpn_efficiency_x ~ group * actamp, data = d))##
## Call:
## lm(formula = fpn_efficiency_x ~ group * actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.84272 -0.19379 -0.01241 0.18439 1.07880
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.67933 0.37058 7.230 5.08e-10 ***
## group1 -0.16719 0.49634 -0.337 0.737
## actamp 0.14999 0.23442 0.640 0.524
## group1:actamp 0.03739 0.31792 0.118 0.907
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3454 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.0456, Adjusted R-squared: 0.004102
## F-statistic: 1.099 on 3 and 69 DF, p-value: 0.3556summary(lm(fpn_clustering_x ~ group * actamp, data = d))##
## Call:
## lm(formula = fpn_clustering_x ~ group * actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.071672 -0.023188 0.007212 0.019586 0.074209
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3075678 0.0346799 8.869 5.17e-13 ***
## group1 0.0070893 0.0464489 0.153 0.879
## actamp -0.0131972 0.0219375 -0.602 0.549
## group1:actamp 0.0008028 0.0297519 0.027 0.979
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03232 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.03008, Adjusted R-squared: -0.01209
## F-statistic: 0.7133 on 3 and 69 DF, p-value: 0.5474summary(lm(fpn_participation_x ~ group * actamp, data = d)) # **##
## Call:
## lm(formula = fpn_participation_x ~ group * actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.21472 -0.03441 0.01477 0.04464 0.14166
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.79657 0.07461 10.676 2.94e-16 ***
## group1 -0.23068 0.09993 -2.308 0.02398 *
## actamp -0.12911 0.04720 -2.735 0.00791 **
## group1:actamp 0.16999 0.06401 2.656 0.00982 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06955 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.1528, Adjusted R-squared: 0.116
## F-statistic: 4.149 on 3 and 69 DF, p-value: 0.009204summary(lm(fpn_modularity_x ~ group + actamp, data = d))##
## Call:
## lm(formula = fpn_modularity_x ~ group + actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.143693 -0.038863 0.005236 0.044023 0.110046
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.382388 0.047218 8.098 1.2e-11 ***
## group1 -0.010570 0.015204 -0.695 0.489
## actamp 0.005945 0.029489 0.202 0.841
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06432 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.007905, Adjusted R-squared: -0.02044
## F-statistic: 0.2789 on 2 and 70 DF, p-value: 0.7575summary(lm(fpn_efficiency_x ~ group + actamp, data = d))##
## Call:
## lm(formula = fpn_efficiency_x ~ group + actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.84211 -0.19284 -0.01694 0.18221 1.07195
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.64754 0.25176 10.516 4.73e-16 ***
## group1 -0.10961 0.08107 -1.352 0.181
## actamp 0.17032 0.15723 1.083 0.282
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.343 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.04541, Adjusted R-squared: 0.01813
## F-statistic: 1.665 on 2 and 70 DF, p-value: 0.1966summary(lm(fpn_clustering_x ~ group + actamp, data = d))##
## Call:
## lm(formula = fpn_clustering_x ~ group + actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.071581 -0.023257 0.007259 0.019539 0.074228
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.306885 0.023558 13.027 <2e-16 ***
## group1 0.008326 0.007586 1.098 0.276
## actamp -0.012761 0.014713 -0.867 0.389
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03209 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.03007, Adjusted R-squared: 0.002357
## F-statistic: 1.085 on 2 and 70 DF, p-value: 0.3435#---------------------------------------------------------
summary(lm(fpn_modularity_x ~ group * actphi, data = d)) # *##
## Call:
## lm(formula = fpn_modularity_x ~ group * actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.149322 -0.048833 0.004452 0.042657 0.104679
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.096351 0.110819 0.869 0.38762
## group1 0.361334 0.154279 2.342 0.02207 *
## actphi 0.017999 0.006728 2.675 0.00932 **
## group1:actphi -0.023163 0.009835 -2.355 0.02137 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06148 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.1067, Adjusted R-squared: 0.06786
## F-statistic: 2.747 on 3 and 69 DF, p-value: 0.04942summary(lm(fpn_efficiency_x ~ group * actphi, data = d))##
## Call:
## lm(formula = fpn_efficiency_x ~ group * actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.82828 -0.21613 -0.02681 0.17525 1.12499
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.039576 0.627522 4.844 7.53e-06 ***
## group1 -0.362602 0.873620 -0.415 0.679
## actphi -0.007662 0.038096 -0.201 0.841
## group1:actphi 0.015618 0.055693 0.280 0.780
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3481 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.03051, Adjusted R-squared: -0.01164
## F-statistic: 0.7239 on 3 and 69 DF, p-value: 0.5412summary(lm(fpn_clustering_x ~ group * actphi, data = d)) # *##
## Call:
## lm(formula = fpn_clustering_x ~ group * actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.067691 -0.022372 0.003912 0.018512 0.071636
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.236492 0.056365 4.196 7.96e-05 ***
## group1 0.177466 0.078470 2.262 0.0269 *
## actphi 0.003074 0.003422 0.898 0.3721
## group1:actphi -0.011003 0.005002 -2.200 0.0312 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03127 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.09237, Adjusted R-squared: 0.05291
## F-statistic: 2.341 on 3 and 69 DF, p-value: 0.08083summary(lm(fpn_participation_x ~ group * actphi, data = d)) # *##
## Call:
## lm(formula = fpn_participation_x ~ group * actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.23260 -0.04180 0.01686 0.04158 0.10572
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.822170 0.127057 6.471 1.19e-08 ***
## group1 -0.409835 0.176885 -2.317 0.0235 *
## actphi -0.013863 0.007713 -1.797 0.0767 .
## group1:actphi 0.028329 0.011276 2.512 0.0143 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07049 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.1297, Adjusted R-squared: 0.09188
## F-statistic: 3.428 on 3 and 69 DF, p-value: 0.02174summary(lm(fpn_efficiency_x ~ group + actphi, data = d))##
## Call:
## lm(formula = fpn_efficiency_x ~ group + actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.84638 -0.22266 -0.03174 0.17873 1.12909
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.9196647 0.4562583 6.399 1.53e-08 ***
## group1 -0.1189754 0.0915378 -1.300 0.198
## actphi -0.0003545 0.0276055 -0.013 0.990
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3458 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.02941, Adjusted R-squared: 0.001677
## F-statistic: 1.06 on 2 and 70 DF, p-value: 0.3518#---------------------------------------------------------
summary(lm(fpn_modularity_x ~ group * sleep_time, data = d))##
## Call:
## lm(formula = fpn_modularity_x ~ group * sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.139845 -0.042491 0.006563 0.044560 0.118075
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4257956 0.0688763 6.182 3.57e-08 ***
## group1 -0.1227495 0.0924539 -1.328 0.189
## sleep_time -0.0001038 0.0002074 -0.501 0.618
## group1:sleep_time 0.0003207 0.0002693 1.191 0.238
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06359 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.03409, Adjusted R-squared: -0.006723
## F-statistic: 0.8353 on 3 and 71 DF, p-value: 0.479summary(lm(fpn_efficiency_x ~ group * sleep_time, data = d))##
## Call:
## lm(formula = fpn_efficiency_x ~ group * sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.83060 -0.19883 -0.01336 0.23905 1.04405
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.400808 0.376697 9.028 2.08e-13 ***
## group1 -0.181201 0.505648 -0.358 0.721
## sleep_time -0.001482 0.001134 -1.307 0.196
## group1:sleep_time 0.000200 0.001473 0.136 0.892
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3478 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.08885, Adjusted R-squared: 0.05035
## F-statistic: 2.308 on 3 and 71 DF, p-value: 0.08385summary(lm(fpn_clustering_x ~ group * sleep_time, data = d))##
## Call:
## lm(formula = fpn_clustering_x ~ group * sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.071708 -0.021840 0.005037 0.021193 0.075258
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3340084 0.0350393 9.532 2.46e-14 ***
## group1 -0.0470221 0.0470339 -1.000 0.321
## sleep_time -0.0001433 0.0001055 -1.358 0.179
## group1:sleep_time 0.0001630 0.0001370 1.190 0.238
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03235 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.0376, Adjusted R-squared: -0.00306
## F-statistic: 0.9248 on 3 and 71 DF, p-value: 0.4334summary(lm(fpn_participation_x ~ group * sleep_time, data = d)) # ##
## Call:
## lm(formula = fpn_participation_x ~ group * sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.20699 -0.03674 0.02192 0.04655 0.11940
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3824571 0.0745695 5.129 2.43e-06 ***
## group1 0.2458485 0.1000960 2.456 0.0165 *
## sleep_time 0.0006459 0.0002245 2.877 0.0053 **
## group1:sleep_time -0.0006431 0.0002916 -2.206 0.0306 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06885 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.1547, Adjusted R-squared: 0.119
## F-statistic: 4.332 on 3 and 71 DF, p-value: 0.007328summary(lm(fpn_modularity_x ~ group + sleep_time, data = d))##
## Call:
## lm(formula = fpn_modularity_x ~ group + sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.141727 -0.043545 0.006059 0.049884 0.110718
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.633e-01 4.475e-02 8.119 9.18e-12 ***
## group1 -1.412e-02 1.513e-02 -0.934 0.354
## sleep_time 8.636e-05 1.327e-04 0.651 0.517
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06377 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.0148, Adjusted R-squared: -0.01257
## F-statistic: 0.5407 on 2 and 72 DF, p-value: 0.5847summary(lm(fpn_efficiency_x ~ group + sleep_time, data = d))##
## Call:
## lm(formula = fpn_efficiency_x ~ group + sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.83193 -0.19791 -0.01558 0.23279 1.05087
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.3618309 0.2423508 13.872 <2e-16 ***
## group1 -0.1134442 0.0819274 -1.385 0.1704
## sleep_time -0.0013634 0.0007186 -1.897 0.0618 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3454 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.08861, Adjusted R-squared: 0.0633
## F-statistic: 3.5 on 2 and 72 DF, p-value: 0.03543summary(lm(fpn_clustering_x ~ group + sleep_time, data = d))##
## Call:
## lm(formula = fpn_clustering_x ~ group + sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.075377 -0.023381 0.005328 0.019689 0.076173
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.023e-01 2.276e-02 13.278 <2e-16 ***
## group1 8.182e-03 7.695e-03 1.063 0.291
## sleep_time -4.663e-05 6.750e-05 -0.691 0.492
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03244 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.01842, Adjusted R-squared: -0.008845
## F-statistic: 0.6756 on 2 and 72 DF, p-value: 0.512#---------------------------------------------------------
summary(lm(fpn_modularity_x ~ group * efficiency, data = d))##
## Call:
## lm(formula = fpn_modularity_x ~ group * efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.14106 -0.03892 0.00468 0.04901 0.11089
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4048181 0.1187170 3.410 0.00108 **
## group1 -0.0953104 0.1628305 -0.585 0.56018
## efficiency -0.0001831 0.0016492 -0.111 0.91190
## group1:efficiency 0.0011558 0.0022542 0.513 0.60973
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06422 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.01473, Adjusted R-squared: -0.0269
## F-statistic: 0.3538 on 3 and 71 DF, p-value: 0.7865summary(lm(fpn_efficiency_x ~ group * efficiency, data = d))##
## Call:
## lm(formula = fpn_efficiency_x ~ group * efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.84956 -0.17832 -0.01858 0.16903 1.11735
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.729961 0.654660 4.170 8.49e-05 ***
## group1 0.593322 0.897922 0.661 0.511
## efficiency 0.002564 0.009095 0.282 0.779
## group1:efficiency -0.010279 0.012431 -0.827 0.411
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3542 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.05514, Adjusted R-squared: 0.01521
## F-statistic: 1.381 on 3 and 71 DF, p-value: 0.2556summary(lm(fpn_clustering_x ~ group * efficiency, data = d)) # ##
## Call:
## lm(formula = fpn_clustering_x ~ group * efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.072255 -0.019434 0.003844 0.022802 0.074609
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4546363 0.0571713 7.952 2.05e-11 ***
## group1 -0.1758022 0.0784153 -2.242 0.02809 *
## efficiency -0.0023383 0.0007942 -2.944 0.00437 **
## group1:efficiency 0.0025478 0.0010856 2.347 0.02172 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03093 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.1203, Adjusted R-squared: 0.08314
## F-statistic: 3.237 on 3 and 71 DF, p-value: 0.02719summary(lm(fpn_participation_x ~ group * efficiency, data = d))##
## Call:
## lm(formula = fpn_participation_x ~ group * efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.25452 -0.03968 0.02329 0.04250 0.10905
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.493655 0.133927 3.686 0.000442 ***
## group1 0.124353 0.183692 0.677 0.500629
## efficiency 0.001409 0.001861 0.757 0.451437
## group1:efficiency -0.001252 0.002543 -0.492 0.623926
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07245 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.06384, Adjusted R-squared: 0.02428
## F-statistic: 1.614 on 3 and 71 DF, p-value: 0.1938summary(lm(fpn_modularity_x ~ group + efficiency, data = d))##
## Call:
## lm(formula = fpn_modularity_x ~ group + efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.142118 -0.042378 0.006454 0.047159 0.109121
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3604468 0.0808528 4.458 2.98e-05 ***
## group1 -0.0121705 0.0147975 -0.822 0.414
## efficiency 0.0004355 0.0011185 0.389 0.698
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06389 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.01108, Adjusted R-squared: -0.01639
## F-statistic: 0.4034 on 2 and 72 DF, p-value: 0.6695summary(lm(fpn_efficiency_x ~ group + efficiency, data = d))##
## Call:
## lm(formula = fpn_efficiency_x ~ group + efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.84461 -0.19852 -0.01795 0.18429 1.14297
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.124576 0.447174 6.987 1.17e-09 ***
## group1 -0.146079 0.081841 -1.785 0.0785 .
## efficiency -0.002938 0.006186 -0.475 0.6362
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3534 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.04604, Adjusted R-squared: 0.01954
## F-statistic: 1.737 on 2 and 72 DF, p-value: 0.1833summary(lm(fpn_participation_x ~ group + efficiency, data = d))##
## Call:
## lm(formula = fpn_participation_x ~ group + efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.25356 -0.03813 0.02255 0.04318 0.11459
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.5417301 0.0911987 5.940 9.26e-08 ***
## group1 0.0342733 0.0166910 2.053 0.0437 *
## efficiency 0.0007385 0.0012616 0.585 0.5602
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07207 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.06064, Adjusted R-squared: 0.03455
## F-statistic: 2.324 on 2 and 72 DF, p-value: 0.1052#---------------------------------------------------------
summary(lm(fpn_modularity_x ~ group * total_ac, data = d))##
## Call:
## lm(formula = fpn_modularity_x ~ group * total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.142650 -0.042525 0.008982 0.050319 0.111095
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.004e-01 2.536e-02 15.789 <2e-16 ***
## group1 -1.838e-03 4.489e-02 -0.041 0.967
## total_ac -5.803e-08 1.544e-07 -0.376 0.708
## group1:total_ac -8.882e-08 3.159e-07 -0.281 0.779
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06422 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.0149, Adjusted R-squared: -0.02672
## F-statistic: 0.358 on 3 and 71 DF, p-value: 0.7835summary(lm(fpn_efficiency_x ~ group * total_ac, data = d))##
## Call:
## lm(formula = fpn_efficiency_x ~ group * total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.83603 -0.20011 -0.01572 0.21757 1.12379
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.867e+00 1.372e-01 20.907 <2e-16 ***
## group1 -4.665e-01 2.428e-01 -1.922 0.0586 .
## total_ac 3.080e-07 8.349e-07 0.369 0.7133
## group1:total_ac 2.536e-06 1.708e-06 1.485 0.1420
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3473 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.0914, Adjusted R-squared: 0.05301
## F-statistic: 2.381 on 3 and 71 DF, p-value: 0.07674summary(lm(fpn_clustering_x ~ group * total_ac, data = d))##
## Call:
## lm(formula = fpn_clustering_x ~ group * total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.072743 -0.021272 0.005475 0.020875 0.074510
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.723e-01 1.280e-02 21.271 <2e-16 ***
## group1 2.562e-02 2.266e-02 1.131 0.262
## total_ac 9.729e-08 7.792e-08 1.249 0.216
## group1:total_ac -1.281e-07 1.594e-07 -0.803 0.424
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03241 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.0338, Adjusted R-squared: -0.007027
## F-statistic: 0.8279 on 3 and 71 DF, p-value: 0.4829summary(lm(fpn_participation_x ~ group * total_ac, data = d))##
## Call:
## lm(formula = fpn_participation_x ~ group * total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.24756 -0.03785 0.02232 0.04113 0.11815
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.178e-01 2.857e-02 21.623 <2e-16 ***
## group1 5.337e-03 5.057e-02 0.106 0.916
## total_ac -1.532e-07 1.739e-07 -0.881 0.381
## group1:total_ac 2.015e-07 3.558e-07 0.566 0.573
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07234 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.06669, Adjusted R-squared: 0.02726
## F-statistic: 1.691 on 3 and 71 DF, p-value: 0.1767summary(lm(fpn_modularity_x ~ group + total_ac, data = d))##
## Call:
## lm(formula = fpn_modularity_x ~ group + total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.14280 -0.04105 0.00705 0.04948 0.10868
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.036e-01 2.253e-02 17.914 <2e-16 ***
## group1 -1.372e-02 1.506e-02 -0.911 0.365
## total_ac -7.924e-08 1.338e-07 -0.592 0.556
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.06381 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.0138, Adjusted R-squared: -0.01359
## F-statistic: 0.5039 on 2 and 72 DF, p-value: 0.6063summary(lm(fpn_efficiency_x ~ group + total_ac, data = d))##
## Call:
## lm(formula = fpn_efficiency_x ~ group + total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.81396 -0.21337 -0.02035 0.21833 1.11298
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.776e+00 1.237e-01 22.452 <2e-16 ***
## group1 -1.273e-01 8.265e-02 -1.540 0.128
## total_ac 9.138e-07 7.344e-07 1.244 0.217
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3502 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.06319, Adjusted R-squared: 0.03717
## F-statistic: 2.428 on 2 and 72 DF, p-value: 0.09538summary(lm(fpn_clustering_x ~ group + total_ac, data = d))##
## Call:
## lm(formula = fpn_clustering_x ~ group + total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.072916 -0.023746 0.006168 0.020668 0.077739
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.769e-01 1.142e-02 24.252 <2e-16 ***
## group1 8.491e-03 7.632e-03 1.113 0.270
## total_ac 6.669e-08 6.781e-08 0.984 0.329
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03233 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.02502, Adjusted R-squared: -0.002068
## F-statistic: 0.9237 on 2 and 72 DF, p-value: 0.4017summary(lm(fpn_participation_x ~ group + total_ac, data = d))##
## Call:
## lm(formula = fpn_participation_x ~ group + total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.24912 -0.03742 0.02277 0.04299 0.11895
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.105e-01 2.542e-02 24.014 <2e-16 ***
## group1 3.230e-02 1.699e-02 1.900 0.0614 .
## total_ac -1.051e-07 1.510e-07 -0.696 0.4888
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.072 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.06247, Adjusted R-squared: 0.03643
## F-statistic: 2.399 on 2 and 72 DF, p-value: 0.09804summary(lm(wb_modularity_x ~ group * IS, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group * IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.208184 -0.043571 0.009253 0.056177 0.127095
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.43298 0.04731 9.152 1.39e-13 ***
## group1 -0.02496 0.06432 -0.388 0.699
## IS -0.05450 0.11515 -0.473 0.637
## group1:IS 0.07055 0.14523 0.486 0.629
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07429 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.004524, Adjusted R-squared: -0.03814
## F-statistic: 0.106 on 3 and 70 DF, p-value: 0.9563summary(lm(wb_efficiency_x ~ group * IS, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group * IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0240 -0.2466 -0.1117 0.2580 1.4253
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.9841 0.2806 10.635 2.9e-16 ***
## group1 -0.2333 0.3815 -0.612 0.543
## IS 0.5568 0.6829 0.815 0.418
## group1:IS -0.2493 0.8613 -0.289 0.773
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4406 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.1262, Adjusted R-squared: 0.0888
## F-statistic: 3.371 on 3 and 70 DF, p-value: 0.02319summary(lm(wb_clustering_x ~ group * IS, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group * IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.103275 -0.026542 0.002192 0.028193 0.059429
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.21140 0.02242 9.430 4.32e-14 ***
## group1 0.02229 0.03048 0.731 0.467
## IS 0.04078 0.05456 0.747 0.457
## group1:IS -0.04833 0.06881 -0.702 0.485
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0352 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.009681, Adjusted R-squared: -0.03276
## F-statistic: 0.2281 on 3 and 70 DF, p-value: 0.8765summary(lm(wb_participation_x ~ group * IS, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group * IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.090206 -0.022556 0.000652 0.021011 0.087680
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.55518 0.02213 25.092 <2e-16 ***
## group1 -0.02280 0.03008 -0.758 0.451
## IS -0.03861 0.05385 -0.717 0.476
## group1:IS 0.08692 0.06792 1.280 0.205
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03474 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.07221, Adjusted R-squared: 0.03245
## F-statistic: 1.816 on 3 and 70 DF, p-value: 0.1522summary(lm(wb_modularity_x ~ group + IS, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group + IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.213708 -0.042502 0.008059 0.054924 0.121074
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.415327 0.030134 13.783 <2e-16 ***
## group1 0.005027 0.017971 0.280 0.781
## IS -0.010148 0.069791 -0.145 0.885
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07389 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.001168, Adjusted R-squared: -0.02697
## F-statistic: 0.04151 on 2 and 71 DF, p-value: 0.9594summary(lm(wb_efficiency_x ~ group + IS, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group + IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0315 -0.2455 -0.1144 0.2379 1.4413
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.0465 0.1785 17.065 < 2e-16 ***
## group1 -0.3393 0.1065 -3.187 0.00214 **
## IS 0.4000 0.4135 0.968 0.33656
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4377 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.1252, Adjusted R-squared: 0.1006
## F-statistic: 5.081 on 2 and 71 DF, p-value: 0.008664summary(lm(wb_clustering_x ~ group + IS, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group + IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.104734 -0.025737 0.002164 0.027571 0.060521
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.22349 0.01430 15.624 <2e-16 ***
## group1 0.00175 0.00853 0.205 0.838
## IS 0.01040 0.03313 0.314 0.755
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03507 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.002704, Adjusted R-squared: -0.02539
## F-statistic: 0.09624 on 2 and 71 DF, p-value: 0.9084summary(lm(wb_participation_x ~ group + IS, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group + IS, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.087583 -0.022095 0.000098 0.021498 0.082652
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.533434 0.014233 37.479 <2e-16 ***
## group1 0.014148 0.008488 1.667 0.0999 .
## IS 0.016033 0.032964 0.486 0.6282
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0349 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.05051, Adjusted R-squared: 0.02376
## F-statistic: 1.888 on 2 and 71 DF, p-value: 0.1589#---------------------------------------------------------
summary(lm(wb_modularity_x ~ group * IV, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group * IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.19311 -0.04350 0.01030 0.05611 0.12196
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.38635 0.04542 8.505 2.14e-12 ***
## group1 0.06618 0.06348 1.043 0.301
## IV 0.02723 0.04795 0.568 0.572
## group1:IV -0.07020 0.06884 -1.020 0.311
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07386 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.01604, Adjusted R-squared: -0.02613
## F-statistic: 0.3804 on 3 and 70 DF, p-value: 0.7674summary(lm(wb_efficiency_x ~ group * IV, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group * IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.85968 -0.26597 -0.07338 0.25043 1.46754
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.5822 0.2668 13.429 <2e-16 ***
## group1 -0.4211 0.3728 -1.129 0.263
## IV -0.4113 0.2816 -1.461 0.149
## group1:IV 0.1025 0.4043 0.254 0.801
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4338 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.1532, Adjusted R-squared: 0.1169
## F-statistic: 4.221 on 3 and 70 DF, p-value: 0.008406summary(lm(wb_clustering_x ~ group * IV, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group * IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.095980 -0.027021 0.000903 0.027929 0.058934
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.245864 0.021597 11.384 <2e-16 ***
## group1 -0.007546 0.030180 -0.250 0.803
## IV -0.019920 0.022797 -0.874 0.385
## group1:IV 0.010408 0.032729 0.318 0.751
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03512 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.01438, Adjusted R-squared: -0.02786
## F-statistic: 0.3404 on 3 and 70 DF, p-value: 0.7961summary(lm(wb_participation_x ~ group * IV, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group * IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.088354 -0.022207 0.000874 0.025563 0.084129
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.398e-01 2.160e-02 24.994 <2e-16 ***
## group1 3.182e-03 3.018e-02 0.105 0.916
## IV 4.267e-05 2.280e-02 0.002 0.999
## group1:IV 1.411e-02 3.273e-02 0.431 0.668
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03512 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.05226, Adjusted R-squared: 0.01164
## F-statistic: 1.287 on 3 and 70 DF, p-value: 0.2858summary(lm(wb_modularity_x ~ group + IV, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group + IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.208636 -0.041381 0.007075 0.053277 0.120649
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.417535 0.033602 12.426 <2e-16 ***
## group1 0.003911 0.017338 0.226 0.822
## IV -0.006824 0.034414 -0.198 0.843
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07388 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.001423, Adjusted R-squared: -0.02671
## F-statistic: 0.0506 on 2 and 71 DF, p-value: 0.9507summary(lm(wb_efficiency_x ~ group + IV, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group + IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.88279 -0.28020 -0.06851 0.24184 1.46931
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.5367 0.1960 18.047 < 2e-16 ***
## group1 -0.3301 0.1011 -3.264 0.00169 **
## IV -0.3615 0.2007 -1.801 0.07592 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4309 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.1524, Adjusted R-squared: 0.1285
## F-statistic: 6.383 on 2 and 71 DF, p-value: 0.002823summary(lm(wb_clustering_x ~ group + IV, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group + IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.098325 -0.027222 0.000333 0.027886 0.058397
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.241241 0.015870 15.201 <2e-16 ***
## group1 0.001687 0.008189 0.206 0.837
## IV -0.014870 0.016253 -0.915 0.363
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03489 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.01296, Adjusted R-squared: -0.01485
## F-statistic: 0.466 on 2 and 71 DF, p-value: 0.6294summary(lm(wb_participation_x ~ group + IV, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group + IV, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.088453 -0.021964 0.001651 0.023980 0.084441
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.533510 0.015879 33.598 <2e-16 ***
## group1 0.015697 0.008193 1.916 0.0594 .
## IV 0.006887 0.016263 0.423 0.6732
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03491 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.04974, Adjusted R-squared: 0.02297
## F-statistic: 1.858 on 2 and 71 DF, p-value: 0.1634#---------------------------------------------------------
summary(lm(wb_modularity_x ~ group * RA, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group * RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.16770 -0.04748 0.01921 0.05028 0.11370
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.33433 0.06435 5.195 1.92e-06 ***
## group1 -0.06949 0.09598 -0.724 0.471
## RA 0.09165 0.07544 1.215 0.229
## group1:RA 0.08837 0.11274 0.784 0.436
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07139 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.08087, Adjusted R-squared: 0.04148
## F-statistic: 2.053 on 3 and 70 DF, p-value: 0.1143summary(lm(wb_efficiency_x ~ group * RA, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group * RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.06869 -0.25336 -0.09223 0.21883 1.54274
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.71328 0.39030 9.514 3.04e-14 ***
## group1 -0.24850 0.58213 -0.427 0.671
## RA -0.60441 0.45758 -1.321 0.191
## group1:RA -0.07535 0.68378 -0.110 0.913
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.433 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.1563, Adjusted R-squared: 0.1201
## F-statistic: 4.322 on 3 and 70 DF, p-value: 0.007459summary(lm(wb_clustering_x ~ group * RA, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group * RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.106156 -0.023331 -0.000377 0.026663 0.063877
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.25368 0.03130 8.104 1.18e-11 ***
## group1 0.02243 0.04669 0.480 0.632
## RA -0.03103 0.03670 -0.845 0.401
## group1:RA -0.02388 0.05484 -0.435 0.665
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03473 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.03615, Adjusted R-squared: -0.005156
## F-statistic: 0.8752 on 3 and 70 DF, p-value: 0.4582summary(lm(wb_participation_x ~ group * RA, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group * RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.092803 -0.023001 0.000397 0.021547 0.087756
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.56321 0.03009 18.718 <2e-16 ***
## group1 -0.09643 0.04488 -2.149 0.0351 *
## RA -0.02786 0.03528 -0.790 0.4324
## group1:RA 0.13338 0.05271 2.530 0.0137 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03338 on 70 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.1437, Adjusted R-squared: 0.107
## F-statistic: 3.917 on 3 and 70 DF, p-value: 0.01206summary(lm(wb_modularity_x ~ group + RA, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group + RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.17206 -0.04517 0.01925 0.05078 0.11180
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.301095 0.048281 6.236 2.85e-08 ***
## group1 0.004602 0.016607 0.277 0.7825
## RA 0.131222 0.055910 2.347 0.0217 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07119 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.07281, Adjusted R-squared: 0.04669
## F-statistic: 2.788 on 2 and 71 DF, p-value: 0.06832summary(lm(wb_efficiency_x ~ group + RA, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group + RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.06970 -0.25082 -0.09276 0.21782 1.54612
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.7416 0.2916 12.832 < 2e-16 ***
## group1 -0.3117 0.1003 -3.108 0.00271 **
## RA -0.6382 0.3377 -1.890 0.06284 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4299 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.1561, Adjusted R-squared: 0.1324
## F-statistic: 6.568 on 2 and 71 DF, p-value: 0.002415summary(lm(wb_clustering_x ~ group + RA, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group + RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.106474 -0.023172 -0.000414 0.026037 0.062919
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.262661 0.023416 11.217 <2e-16 ***
## group1 0.002408 0.008054 0.299 0.766
## RA -0.041719 0.027116 -1.539 0.128
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03453 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.03354, Adjusted R-squared: 0.006318
## F-statistic: 1.232 on 2 and 71 DF, p-value: 0.2978summary(lm(wb_participation_x ~ group + RA, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group + RA, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.083261 -0.021906 -0.000124 0.020854 0.079976
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.513051 0.023482 21.849 <2e-16 ***
## group1 0.015393 0.008077 1.906 0.0607 .
## RA 0.031872 0.027192 1.172 0.2451
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03462 on 71 degrees of freedom
## (60 observations deleted due to missingness)
## Multiple R-squared: 0.06542, Adjusted R-squared: 0.0391
## F-statistic: 2.485 on 2 and 71 DF, p-value: 0.09053#---------------------------------------------------------
summary(lm(wb_modularity_x ~ group * fact, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group * fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.22026 -0.04373 0.01265 0.05371 0.13300
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.336e-01 2.927e-02 14.811 <2e-16 ***
## group1 -7.361e-03 4.198e-02 -0.175 0.861
## fact -5.463e-06 6.577e-06 -0.831 0.409
## group1:fact 3.334e-06 9.005e-06 0.370 0.712
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07437 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.013, Adjusted R-squared: -0.02992
## F-statistic: 0.3028 on 3 and 69 DF, p-value: 0.8232summary(lm(wb_efficiency_x ~ group * fact, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group * fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.00847 -0.23542 -0.05151 0.22577 1.41801
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.084e+00 1.703e-01 18.109 <2e-16 ***
## group1 -4.652e-01 2.442e-01 -1.905 0.0609 .
## fact 2.994e-05 3.826e-05 0.782 0.4366
## group1:fact 3.529e-05 5.238e-05 0.674 0.5028
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4326 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.1543, Adjusted R-squared: 0.1175
## F-statistic: 4.195 on 3 and 69 DF, p-value: 0.008716summary(lm(wb_clustering_x ~ group * fact, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group * fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.10277 -0.02508 0.00199 0.02837 0.05837
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.205e-01 1.393e-02 15.829 <2e-16 ***
## group1 1.279e-02 1.998e-02 0.640 0.524
## fact 1.744e-06 3.130e-06 0.557 0.579
## group1:fact -2.298e-06 4.286e-06 -0.536 0.594
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03539 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.007162, Adjusted R-squared: -0.03601
## F-statistic: 0.1659 on 3 and 69 DF, p-value: 0.919summary(lm(wb_participation_x ~ group * fact, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group * fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.088570 -0.022147 -0.000284 0.021492 0.084846
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.406e-01 1.347e-02 40.135 <2e-16 ***
## group1 -4.818e-03 1.932e-02 -0.249 0.804
## fact -1.908e-07 3.027e-06 -0.063 0.950
## group1:fact 4.166e-06 4.144e-06 1.005 0.318
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03422 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.06499, Adjusted R-squared: 0.02434
## F-statistic: 1.599 on 3 and 69 DF, p-value: 0.1976summary(lm(wb_modularity_x ~ group + fact, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group + fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.225718 -0.042275 0.008414 0.055371 0.127847
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.263e-01 2.163e-02 19.712 <2e-16 ***
## group1 6.756e-03 1.745e-02 0.387 0.700
## fact -3.684e-06 4.465e-06 -0.825 0.412
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07391 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.01104, Adjusted R-squared: -0.01722
## F-statistic: 0.3905 on 2 and 70 DF, p-value: 0.6782summary(lm(wb_efficiency_x ~ group + fact, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group + fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.98192 -0.26288 -0.07033 0.21467 1.37768
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.007e+00 1.261e-01 23.848 < 2e-16 ***
## group1 -3.158e-01 1.017e-01 -3.104 0.00275 **
## fact 4.876e-05 2.603e-05 1.873 0.06520 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4309 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.1487, Adjusted R-squared: 0.1244
## F-statistic: 6.113 on 2 and 70 DF, p-value: 0.003573summary(lm(wb_clustering_x ~ group + fact, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group + fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.104501 -0.025242 0.002023 0.028074 0.059896
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.255e-01 1.030e-02 21.888 <2e-16 ***
## group1 3.063e-03 8.312e-03 0.369 0.714
## fact 5.185e-07 2.127e-06 0.244 0.808
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03521 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.003026, Adjusted R-squared: -0.02546
## F-statistic: 0.1062 on 2 and 70 DF, p-value: 0.8994summary(lm(wb_participation_x ~ group + fact, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group + fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.086045 -0.023090 -0.000936 0.019968 0.076481
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.315e-01 1.001e-02 53.081 <2e-16 ***
## group1 1.282e-02 8.079e-03 1.587 0.117
## fact 2.031e-06 2.067e-06 0.983 0.329
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03422 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.05129, Adjusted R-squared: 0.02419
## F-statistic: 1.892 on 2 and 70 DF, p-value: 0.1584#---------------------------------------------------------
summary(lm(wb_modularity_x ~ group * actamp, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group * actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.211290 -0.048462 0.009251 0.050565 0.145048
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.54450 0.07860 6.928 1.8e-09 ***
## group1 -0.13213 0.10527 -1.255 0.2137
## actamp -0.08520 0.04972 -1.714 0.0911 .
## group1:actamp 0.08812 0.06743 1.307 0.1956
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07326 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.04223, Adjusted R-squared: 0.0005921
## F-statistic: 1.014 on 3 and 69 DF, p-value: 0.3918summary(lm(wb_efficiency_x ~ group * actamp, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group * actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.03311 -0.25231 -0.07239 0.24181 1.28615
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.2954 0.4606 4.984 4.43e-06 ***
## group1 0.1922 0.6168 0.312 0.7563
## actamp 0.5822 0.2913 1.998 0.0496 *
## group1:actamp -0.3051 0.3951 -0.772 0.4427
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4293 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.1672, Adjusted R-squared: 0.131
## F-statistic: 4.619 on 3 and 69 DF, p-value: 0.005293summary(lm(wb_clustering_x ~ group * actamp, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group * actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.10405 -0.02538 0.00498 0.02738 0.07399
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.16668 0.03727 4.473 2.96e-05 ***
## group1 0.08089 0.04991 1.621 0.110
## actamp 0.03898 0.02357 1.654 0.103
## group1:actamp -0.05003 0.03197 -1.565 0.122
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03473 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.04371, Adjusted R-squared: 0.002127
## F-statistic: 1.051 on 3 and 69 DF, p-value: 0.3756summary(lm(wb_participation_x ~ group * actamp, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group * actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.079717 -0.021283 -0.002828 0.019273 0.088921
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.58595 0.03592 16.314 <2e-16 ***
## group1 -0.09127 0.04810 -1.897 0.062 .
## actamp -0.02951 0.02272 -1.299 0.198
## group1:actamp 0.06830 0.03081 2.217 0.030 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03348 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.1051, Adjusted R-squared: 0.06622
## F-statistic: 2.702 on 3 and 69 DF, p-value: 0.0522summary(lm(wb_modularity_x ~ group + actamp, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group + actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.23187 -0.04277 0.01191 0.05436 0.12937
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.46960 0.05405 8.689 9.86e-13 ***
## group1 0.00357 0.01740 0.205 0.838
## actamp -0.03729 0.03376 -1.105 0.273
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07363 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.01853, Adjusted R-squared: -0.009513
## F-statistic: 0.6608 on 2 and 70 DF, p-value: 0.5197summary(lm(wb_efficiency_x ~ group + actamp, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group + actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0381 -0.2540 -0.0573 0.2743 1.3420
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.5547 0.3142 8.131 1.05e-11 ***
## group1 -0.2776 0.1012 -2.744 0.0077 **
## actamp 0.4163 0.1962 2.122 0.0374 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.428 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.16, Adjusted R-squared: 0.136
## F-statistic: 6.668 on 2 and 70 DF, p-value: 0.002235summary(lm(wb_clustering_x ~ group + actamp, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group + actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.104876 -0.025971 0.002049 0.026956 0.062811
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.209204 0.025760 8.121 1.09e-11 ***
## group1 0.003850 0.008295 0.464 0.644
## actamp 0.011783 0.016088 0.732 0.466
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03509 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.009767, Adjusted R-squared: -0.01852
## F-statistic: 0.3452 on 2 and 70 DF, p-value: 0.7093summary(lm(wb_participation_x ~ group + actamp, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group + actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.090585 -0.023412 0.000732 0.023682 0.082889
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.527893 0.025251 20.905 <2e-16 ***
## group1 0.013908 0.008131 1.710 0.0916 .
## actamp 0.007625 0.015771 0.484 0.6302
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0344 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.04141, Adjusted R-squared: 0.01402
## F-statistic: 1.512 on 2 and 70 DF, p-value: 0.2276#---------------------------------------------------------
summary(lm(wb_modularity_x ~ group * actphi, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group * actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.209019 -0.041148 0.008544 0.058477 0.122391
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.458294 0.134478 3.408 0.0011 **
## group1 -0.106014 0.187217 -0.566 0.5731
## actphi -0.002865 0.008164 -0.351 0.7267
## group1:actphi 0.007198 0.011935 0.603 0.5484
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.0746 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.006755, Adjusted R-squared: -0.03643
## F-statistic: 0.1564 on 3 and 69 DF, p-value: 0.9252summary(lm(wb_efficiency_x ~ group * actphi, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group * actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0192 -0.2406 -0.1013 0.2918 1.4750
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.41479 0.79436 4.299 5.53e-05 ***
## group1 0.33591 1.10589 0.304 0.762
## actphi -0.01274 0.04822 -0.264 0.792
## group1:actphi -0.04396 0.07050 -0.624 0.535
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4407 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.1224, Adjusted R-squared: 0.08421
## F-statistic: 3.207 on 3 and 69 DF, p-value: 0.02837summary(lm(wb_clustering_x ~ group * actphi, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group * actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.101496 -0.024834 0.001338 0.027954 0.055959
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.252384 0.063247 3.990 0.000162 ***
## group1 0.050674 0.088050 0.576 0.566821
## actphi -0.001509 0.003840 -0.393 0.695567
## group1:actphi -0.003341 0.005613 -0.595 0.553703
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03509 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.0242, Adjusted R-squared: -0.01823
## F-statistic: 0.5704 on 3 and 69 DF, p-value: 0.6364summary(lm(wb_participation_x ~ group * actphi, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group * actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.083502 -0.020964 0.001803 0.021042 0.080478
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.595250 0.060896 9.775 1.18e-14 ***
## group1 -0.143362 0.084777 -1.691 0.0953 .
## actphi -0.003378 0.003697 -0.914 0.3640
## group1:actphi 0.010192 0.005405 1.886 0.0635 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03378 on 69 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.08869, Adjusted R-squared: 0.04907
## F-statistic: 2.238 on 3 and 69 DF, p-value: 0.09149summary(lm(wb_modularity_x ~ group + actphi, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group + actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.212347 -0.042878 0.009458 0.054667 0.120951
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4030287 0.0979778 4.113 0.000105 ***
## group1 0.0062688 0.0196570 0.319 0.750744
## actphi 0.0005034 0.0059281 0.085 0.932575
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07426 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.001519, Adjusted R-squared: -0.02701
## F-statistic: 0.05324 on 2 and 70 DF, p-value: 0.9482summary(lm(wb_efficiency_x ~ group + actphi, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group + actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9682 -0.2485 -0.1034 0.2937 1.4635
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.75233 0.57886 6.482 1.08e-08 ***
## group1 -0.34989 0.11614 -3.013 0.0036 **
## actphi -0.03331 0.03502 -0.951 0.3448
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4388 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.1174, Adjusted R-squared: 0.0922
## F-statistic: 4.656 on 2 and 70 DF, p-value: 0.01263summary(lm(wb_clustering_x ~ group + actphi, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group + actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.097625 -0.025016 0.001984 0.026663 0.058204
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.278032 0.046077 6.034 6.82e-08 ***
## group1 -0.001435 0.009244 -0.155 0.877
## actphi -0.003072 0.002788 -1.102 0.274
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03493 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.01919, Adjusted R-squared: -0.008832
## F-statistic: 0.6848 on 2 and 70 DF, p-value: 0.5075summary(lm(wb_participation_x ~ group + actphi, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group + actphi, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.090350 -0.022181 0.000444 0.024979 0.085630
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.516995 0.045377 11.393 <2e-16 ***
## group1 0.015629 0.009104 1.717 0.0904 .
## actphi 0.001391 0.002745 0.507 0.6141
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03439 on 70 degrees of freedom
## (61 observations deleted due to missingness)
## Multiple R-squared: 0.04172, Adjusted R-squared: 0.01434
## F-statistic: 1.524 on 2 and 70 DF, p-value: 0.225#---------------------------------------------------------
summary(lm(wb_modularity_x ~ group * sleep_time, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group * sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.19544 -0.04638 0.00970 0.04419 0.12932
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2764930 0.0777423 3.557 0.000674 ***
## group1 0.0327767 0.1043550 0.314 0.754375
## sleep_time 0.0004103 0.0002341 1.753 0.083980 .
## group1:sleep_time -0.0001028 0.0003040 -0.338 0.736297
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07178 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.07489, Adjusted R-squared: 0.0358
## F-statistic: 1.916 on 3 and 71 DF, p-value: 0.1348summary(lm(wb_efficiency_x ~ group * sleep_time, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group * sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0039 -0.2935 -0.1046 0.2380 1.2424
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.575575 0.445735 10.265 1.13e-15 ***
## group1 -1.238386 0.598318 -2.070 0.04211 *
## sleep_time -0.004169 0.001342 -3.107 0.00272 **
## group1:sleep_time 0.002894 0.001743 1.661 0.10116
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4115 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.2381, Adjusted R-squared: 0.2059
## F-statistic: 7.397 on 3 and 71 DF, p-value: 0.0002215summary(lm(wb_clustering_x ~ group * sleep_time, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group * sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.101415 -0.023697 0.001451 0.025436 0.067102
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3392422 0.0357120 9.499 2.82e-14 ***
## group1 -0.0869779 0.0479369 -1.814 0.07384 .
## sleep_time -0.0003397 0.0001075 -3.159 0.00232 **
## group1:sleep_time 0.0002743 0.0001396 1.965 0.05338 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03297 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.1295, Adjusted R-squared: 0.09269
## F-statistic: 3.52 on 3 and 71 DF, p-value: 0.01932summary(lm(wb_participation_x ~ group * sleep_time, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group * sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.077689 -0.022672 -0.000063 0.020843 0.076305
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.901e-01 3.725e-02 13.156 <2e-16 ***
## group1 4.100e-02 5.000e-02 0.820 0.415
## sleep_time 1.513e-04 1.122e-04 1.349 0.182
## group1:sleep_time -8.327e-05 1.456e-04 -0.572 0.569
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03439 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.07872, Adjusted R-squared: 0.03979
## F-statistic: 2.022 on 3 and 71 DF, p-value: 0.1185summary(lm(wb_modularity_x ~ group + sleep_time, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group + sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.192925 -0.046353 0.008685 0.040878 0.137285
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.2965163 0.0500498 5.924 9.87e-08 ***
## group1 -0.0020315 0.0169195 -0.120 0.9048
## sleep_time 0.0003493 0.0001484 2.354 0.0213 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07133 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.0734, Adjusted R-squared: 0.04766
## F-statistic: 2.852 on 2 and 72 DF, p-value: 0.06429summary(lm(wb_efficiency_x ~ group + sleep_time, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group + sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.02315 -0.29190 -0.06556 0.28016 1.34108
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.0116151 0.2922461 13.727 < 2e-16 ***
## group1 -0.2580073 0.0987946 -2.612 0.01096 *
## sleep_time -0.0024527 0.0008666 -2.830 0.00602 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4165 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.2085, Adjusted R-squared: 0.1865
## F-statistic: 9.485 on 2 and 72 DF, p-value: 0.0002206summary(lm(wb_clustering_x ~ group + sleep_time, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group + sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.103243 -0.023604 -0.002162 0.023968 0.077737
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.858e-01 2.359e-02 12.116 <2e-16 ***
## group1 5.936e-03 7.974e-03 0.744 0.4591
## sleep_time -1.770e-04 6.995e-05 -2.531 0.0136 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03362 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.08215, Adjusted R-squared: 0.05665
## F-statistic: 3.222 on 2 and 72 DF, p-value: 0.04569summary(lm(wb_participation_x ~ group + sleep_time, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group + sleep_time, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.081169 -0.022639 -0.000012 0.022236 0.078857
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.063e-01 2.402e-02 21.081 <2e-16 ***
## group1 1.279e-02 8.119e-03 1.575 0.120
## sleep_time 1.020e-04 7.122e-05 1.432 0.157
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03423 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.07448, Adjusted R-squared: 0.04877
## F-statistic: 2.897 on 2 and 72 DF, p-value: 0.06165#---------------------------------------------------------
summary(lm(wb_modularity_x ~ group * efficiency, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group * efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.209852 -0.044391 0.009905 0.053546 0.120870
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.279994 0.136840 2.046 0.0444 *
## group1 0.104516 0.187687 0.557 0.5794
## efficiency 0.001831 0.001901 0.963 0.3388
## group1:efficiency -0.001367 0.002598 -0.526 0.6004
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07403 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.01591, Adjusted R-squared: -0.02568
## F-statistic: 0.3825 on 3 and 71 DF, p-value: 0.7659summary(lm(wb_efficiency_x ~ group * efficiency, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group * efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.03525 -0.28132 -0.07924 0.21062 1.56212
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.43758 0.80325 5.525 5.13e-07 ***
## group1 -1.26970 1.10173 -1.152 0.253
## efficiency -0.01718 0.01116 -1.539 0.128
## group1:efficiency 0.01328 0.01525 0.871 0.387
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4345 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.1505, Adjusted R-squared: 0.1146
## F-statistic: 4.193 on 3 and 71 DF, p-value: 0.008643summary(lm(wb_clustering_x ~ group * efficiency, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group * efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.103783 -0.026010 -0.001073 0.026582 0.064212
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3431103 0.0631793 5.431 7.44e-07 ***
## group1 -0.0418171 0.0866557 -0.483 0.6309
## efficiency -0.0016102 0.0008777 -1.835 0.0708 .
## group1:efficiency 0.0006107 0.0011996 0.509 0.6123
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03418 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.06452, Adjusted R-squared: 0.02499
## F-statistic: 1.632 on 3 and 71 DF, p-value: 0.1896summary(lm(wb_participation_x ~ group * efficiency, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group * efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.089014 -0.020775 0.000883 0.022435 0.080310
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.5066919 0.0636154 7.965 1.94e-11 ***
## group1 -0.0352984 0.0872539 -0.405 0.687
## efficiency 0.0004619 0.0008838 0.523 0.603
## group1:efficiency 0.0006985 0.0012079 0.578 0.565
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03441 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.07748, Adjusted R-squared: 0.0385
## F-statistic: 1.988 on 3 and 71 DF, p-value: 0.1236summary(lm(wb_modularity_x ~ group + efficiency, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group + efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.204226 -0.045892 0.007179 0.056812 0.119444
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.332480 0.093205 3.567 0.000646 ***
## group1 0.006171 0.017058 0.362 0.718605
## efficiency 0.001099 0.001289 0.852 0.396920
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07366 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.01207, Adjusted R-squared: -0.01537
## F-statistic: 0.4398 on 2 and 72 DF, p-value: 0.6459summary(lm(wb_efficiency_x ~ group + efficiency, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group + efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0416 -0.2806 -0.1041 0.2616 1.5290
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.927800 0.548956 7.155 5.72e-10 ***
## group1 -0.314520 0.100469 -3.131 0.00252 **
## efficiency -0.010068 0.007594 -1.326 0.18912
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4338 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.1414, Adjusted R-squared: 0.1176
## F-statistic: 5.93 on 2 and 72 DF, p-value: 0.004131summary(lm(wb_clustering_x ~ group + efficiency, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group + efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.104078 -0.026216 -0.000067 0.026204 0.063711
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3196655 0.0430274 7.429 1.77e-10 ***
## group1 0.0021122 0.0078748 0.268 0.7893
## efficiency -0.0012833 0.0005952 -2.156 0.0344 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.034 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.0611, Adjusted R-squared: 0.03502
## F-statistic: 2.343 on 2 and 72 DF, p-value: 0.1033summary(lm(wb_participation_x ~ group + efficiency, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group + efficiency, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.089550 -0.021887 -0.000356 0.021168 0.077220
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.4798759 0.0433473 11.070 <2e-16 ***
## group1 0.0149474 0.0079333 1.884 0.0636 .
## efficiency 0.0008358 0.0005997 1.394 0.1677
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03426 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.07314, Adjusted R-squared: 0.04739
## F-statistic: 2.841 on 2 and 72 DF, p-value: 0.06495#---------------------------------------------------------
summary(lm(wb_modularity_x ~ group * total_ac, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group * total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.17886 -0.05088 0.01280 0.05125 0.11686
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.607e-01 2.788e-02 16.526 <2e-16 ***
## group1 3.937e-02 4.934e-02 0.798 0.4276
## total_ac -3.281e-07 1.697e-07 -1.933 0.0572 .
## group1:total_ac -3.107e-07 3.472e-07 -0.895 0.3738
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07059 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.1053, Adjusted R-squared: 0.06746
## F-statistic: 2.784 on 3 and 71 DF, p-value: 0.04702summary(lm(wb_efficiency_x ~ group * total_ac, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group * total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.95626 -0.24882 -0.04928 0.23203 1.43588
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.815e+00 1.625e-01 17.327 <2e-16 ***
## group1 -3.898e-01 2.876e-01 -1.355 0.1796
## total_ac 2.592e-06 9.891e-07 2.621 0.0107 *
## group1:total_ac 9.943e-07 2.024e-06 0.491 0.6247
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4114 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.2384, Adjusted R-squared: 0.2062
## F-statistic: 7.409 on 3 and 71 DF, p-value: 0.0002186summary(lm(wb_clustering_x ~ group * total_ac, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group * total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.100155 -0.025819 0.001346 0.026926 0.065194
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.066e-01 1.366e-02 15.128 <2e-16 ***
## group1 1.276e-02 2.418e-02 0.528 0.5992
## total_ac 1.394e-07 8.315e-08 1.676 0.0981 .
## group1:total_ac -6.357e-08 1.701e-07 -0.374 0.7098
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03459 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.04191, Adjusted R-squared: 0.001429
## F-statistic: 1.035 on 3 and 71 DF, p-value: 0.3823summary(lm(wb_participation_x ~ group * total_ac, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group * total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.090277 -0.021863 0.000954 0.022384 0.085116
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.308e-01 1.375e-02 38.606 <2e-16 ***
## group1 2.932e-02 2.434e-02 1.205 0.232
## total_ac 5.965e-08 8.370e-08 0.713 0.478
## group1:total_ac -9.860e-08 1.713e-07 -0.576 0.567
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03482 on 71 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.05579, Adjusted R-squared: 0.01589
## F-statistic: 1.398 on 3 and 71 DF, p-value: 0.2504summary(lm(wb_modularity_x ~ group + total_ac, data = d))##
## Call:
## lm(formula = wb_modularity_x ~ group + total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.19185 -0.05267 0.01385 0.04992 0.11678
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.719e-01 2.489e-02 18.958 < 2e-16 ***
## group1 -2.195e-03 1.664e-02 -0.132 0.89541
## total_ac -4.023e-07 1.478e-07 -2.721 0.00815 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.07049 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.09517, Adjusted R-squared: 0.07004
## F-statistic: 3.786 on 2 and 72 DF, p-value: 0.02732summary(lm(wb_efficiency_x ~ group + total_ac, data = d))##
## Call:
## lm(formula = wb_efficiency_x ~ group + total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.94760 -0.23446 -0.04844 0.22636 1.43164
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.780e+00 1.445e-01 19.235 < 2e-16 ***
## group1 -2.567e-01 9.660e-02 -2.658 0.00968 **
## total_ac 2.830e-06 8.583e-07 3.297 0.00152 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4093 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.2358, Adjusted R-squared: 0.2146
## F-statistic: 11.11 on 2 and 72 DF, p-value: 6.236e-05summary(lm(wb_clustering_x ~ group + total_ac, data = d))##
## Call:
## lm(formula = wb_clustering_x ~ group + total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.100708 -0.026059 0.000974 0.026267 0.067953
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.089e-01 1.214e-02 17.210 <2e-16 ***
## group1 4.261e-03 8.115e-03 0.525 0.6011
## total_ac 1.242e-07 7.211e-08 1.722 0.0894 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03438 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.04003, Adjusted R-squared: 0.01336
## F-statistic: 1.501 on 2 and 72 DF, p-value: 0.2298summary(lm(wb_participation_x ~ group + total_ac, data = d))##
## Call:
## lm(formula = wb_participation_x ~ group + total_ac, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.08952 -0.02210 0.00164 0.02457 0.08473
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.344e-01 1.224e-02 43.670 <2e-16 ***
## group1 1.613e-02 8.180e-03 1.972 0.0525 .
## total_ac 3.610e-08 7.268e-08 0.497 0.6209
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.03465 on 72 degrees of freedom
## (59 observations deleted due to missingness)
## Multiple R-squared: 0.05138, Adjusted R-squared: 0.02503
## F-statistic: 1.95 on 2 and 72 DF, p-value: 0.1497d3.mlt <- melt(select(d, record_id, group, dmn_participation_x, IS:fact, -L5_starttime, -M10_starttime, efficiency:total_ac), id.vars=c('record_id', 'group', 'dmn_participation_x'))
ggplot(data = d3.mlt) +
ggtitle('DMN Participation Coefficient and Rest-Activity Measures') +
geom_point(aes(x = value, y = dmn_participation_x, group = group, color = group), size=0.5) +
#stat_smooth(aes(x = value, y = dmn_participation_x, group = group, color = group), method = 'lm', se = FALSE, fullrange = FALSE) +
facet_wrap(~ variable, scales='free') +
theme_minimal() +
scale_color_manual(values = brewer.pal(8, "Paired")[7:8], name = 'Group', labels = c('Young Adults', 'Older Adults')) +
xlab(element_blank()) + ylab('DMN Participation Coefficient') +
theme(axis.text.y = element_blank(), axis.text.x = element_blank())## Warning: Removed 1266 rows containing missing values (geom_point).
ggplot(data = d) +
ggtitle('DMN Participation Coefficient and Amplitude') +
geom_point(aes(x = actamp, y = dmn_participation_x, group = group, color = group), size=2) +
stat_smooth(aes(x = actamp, y = dmn_participation_x, group = group, color = group), method = 'lm', se = FALSE, fullrange = FALSE) +
theme_minimal() +
scale_color_manual(values = brewer.pal(8, "Paired")[7:8], name = 'Group', labels = c('Young Adults', 'Older Adults')) +
xlab('Amplitude') + ylab('DMN Participation Coefficient') ## Warning: Removed 61 rows containing non-finite values (stat_smooth).## Warning: Removed 61 rows containing missing values (geom_point).
ggplot(data = d) +
ggtitle('DMN Participation Coefficient and Interdaily Stability') +
geom_point(aes(x = IS, y = dmn_participation_x, group = group, color = group), size=2) +
stat_smooth(aes(x = IS, y = dmn_participation_x, group = group, color = group), method = 'lm', se = FALSE, fullrange = FALSE) +
theme_minimal() +
scale_color_manual(values = brewer.pal(8, "Paired")[7:8], name = 'Group', labels = c('Young Adults', 'Older Adults')) +
xlab('IS') + ylab('DMN Participation Coefficient') ## Warning: Removed 60 rows containing non-finite values (stat_smooth).## Warning: Removed 60 rows containing missing values (geom_point).
ggplot(data = d) +
ggtitle('DMN Participation Coefficient and Total Sleep Time') +
geom_point(aes(x = sleep_time, y = dmn_participation_x, group = group, color = group), size=2) +
stat_smooth(aes(x = sleep_time, y = dmn_participation_x, group = group, color = group), method = 'lm', se = FALSE, fullrange = FALSE) +
theme_minimal() +
scale_color_manual(values = brewer.pal(8, "Paired")[7:8], name = 'Group', labels = c('Young Adults', 'Older Adults')) +
xlab('Sleep Time (min)') + ylab('DMN Participation Coefficient') +
scale_x_continuous(limits = c(125, 550))## Warning: Removed 59 rows containing non-finite values (stat_smooth).## Warning: Removed 59 rows containing missing values (geom_point).
plot(lm(dmn_participation_x ~ actamp, data = d))
summary(lm(trails_b_z_score ~ group + actamp, data = d))##
## Call:
## lm(formula = trails_b_z_score ~ group + actamp, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.5327 -0.7351 0.1222 1.0960 2.5738
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -3.5357 0.8597 -4.113 7.61e-05 ***
## group1 0.6526 0.2773 2.353 0.020397 *
## actamp 1.9839 0.5345 3.712 0.000326 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.444 on 109 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.1335, Adjusted R-squared: 0.1176
## F-statistic: 8.399 on 2 and 109 DF, p-value: 0.000405plot(lm(trails_b_z_score ~ group + actamp, data = d))
summary(lm(trails_b_z_score ~ group + fact, data = d))##
## Call:
## lm(formula = trails_b_z_score ~ group + fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.9129 -0.6277 0.1647 1.1082 2.2264
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.138e+00 3.525e-01 -3.229 0.00164 **
## group1 4.212e-01 2.830e-01 1.488 0.13953
## fact 1.825e-04 7.421e-05 2.459 0.01549 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.492 on 109 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.07535, Adjusted R-squared: 0.05838
## F-statistic: 4.441 on 2 and 109 DF, p-value: 0.01399summary(lm(trails_b_z_score ~ fact, data = d))##
## Call:
## lm(formula = trails_b_z_score ~ fact, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5.6847 -0.6959 0.1140 1.2130 2.4284
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -9.544e-01 3.320e-01 -2.875 0.00486 **
## fact 1.910e-04 7.439e-05 2.568 0.01158 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.5 on 110 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.05655, Adjusted R-squared: 0.04798
## F-statistic: 6.594 on 1 and 110 DF, p-value: 0.01158plot(lm(trails_b_z_score ~ fact, data = d))
